Dongchu Sun’s Curriculum Vitae CV.pdf · Dongchu Sun’s Curriculum Vitae 25 { 5 8. Luyan Dai (2005). Bayesian Smoothing of Density Estimation via Hazard Rates. 9. Xiaoyan Lin (2005)

Dongchu Sun’s Curriculum Vitae

September 1, 2019

Education

B.S., Math Department of Mathematics, East China Normal University, Shanghai,China. January 1982. GPA 3.96/4.0

M.S., Statistics Department of Statistics, East China Normal University, Shanghai,China. December, 1984. GPA 4.0/4.0

M.S., Statistics Department of Statistics, The Ohio State University, Columbus, Ohio.August 1988. GPA 3.92/4.0

Ph.D., Statistics Department of Statistics, Purdue University, West Lafayette, Indiana.July 1991. Advisor: James O. Berger.Dissertation: Bayesian Sequential Reliability for Weibull and RelatedDistributions.

Positions Held

1/85 – 6/87: Lecturer, Dept of Stat, East China Normal University, Shanghai, China.

9/91 – 7/92: Visiting Assistant Professor of Statistics, the University of Michigan.

8/92 – 7/98: Assistant Professor of Statistics, the University of Missouri-Columbia.

8/98 – 8/02: Associate Professor of Statistics, the University of Missouri-Columbia.

8/98 – 7/99: Senior Research Fellow at the NISS and Duke University.

8/02 – 8/19: Professor of Statistics, University of Missouri-Columbia.

8/11 – 7/18: Chair, Department of Statistics, University of Missouri-Columbia.

8/09 – 7/10: One of the 4 leaders in 2009-10 SAMSI Program on Space-time Analysis forEnvironmental Mapping, Epidemiology and Climate Change.

8/18 – 5/19: co-leader of Data Fusion Working Group in 2018-19 SAMSI Model Uncer-tainty: Mathematical and Statistical (MUMS) Program.

9/19 – Professor Emeritus of Statistics, University of Missouri-Columbia.

9/19 – Research Professor of Statistics, University of Nebraska-Lincoln.

Honors

2000: Elected as an ordinary member of the International Statistical Institute.

2004: Elected Fellow of the American Statistical Association.

2005: Elected Fellow of the Institute of Mathematical Statistics.

Scholarships

1/82: University Scholarship (top 2.5% students among seniors), East China Nor-mal University, Shanghai, China.

7/86 – 6/88: University Fellowship, Department of Statistics, University of California,Berkeley; (I did not accept for family reasons).

9/87 – 8/88: University Fellowship, The Ohio State University.

6/90 – 8/91: David Ross Fellowship, Purdue University.

Dongchu Sun’s Curriculum Vitae 25 – 2

Awards

1987: Award of Scientific Results for Young Researchers, East China Normal University,Shanghai, China.

1991: I.W. Burr Award for Outstanding PhD. Thesis, Purdue University.

1999: Albert Winemiller First Prize for Outstanding Developments of New StatisticalMethodology for an Applied Setting, University of Missouri, The First AppliedStatistics Symposium.

2001: (with J.N. Rouder and P.L. Speckman). Albert Winemiller Prize for OutstandingResearch in Psychological Statistics.

2002: 2002 Chancellors Award for Outstanding Research and Creative Activity in Phys-ical and Math Sciences, University of Missouri-Columbia (a $1,000 cash prize anda $2,000 unrestricted fund for professional activities.)

2007: (with J.N. Rouder, J. Lu, P.L. Speckman, P.L., Morey, and M. Naveh-Benjamin).The 2007 Winemiller Award for significant collaboration between Statistics andPsychology.

2009: (with J.N. Rouder, J. Lu, P.L. Speckman, ). The 2009 Winemiller Award forsignificant collaboration between Statistics and Psychology.

2017: The 2017 Distinguish Science Award, Purdue University.

Teaching Experience Since 1991

University of Michigan, Ann Arbor

STAT100: Introduction to Statistical Reasoning F91, S92

STAT540: Introduction to Nonparametric Statistics S92

STAT425: A First Course in Probability Theory S92

Virginia Tech

STAT5124: Theory of Linear Models S06

University of Missouri–Columbia

STAT31 : Elementary Statistics F94, S95

STAT320: Introduction to Mathematical Statistics F92, F93, F96, F00, S93

STAT321: Bayesian Data Analysis and Applications S02

STAT325: Introduction to Probability Theory S93

STAT385: Regression and Correlation Analysis S95, F95

STAT395: Analysis of Variance F92, F94

STAT403: Mathematical Statistics F99

STAT420: Bayesian Statistics F97, S00, F01, F04

STAT430: Reliability and Survival Analysis F96

STAT440: Probability and Measure Theory F93, F95, F02

STAT441: Introduction to Stochastic Processes S94, S96, S00, S03

STAT461: Bayesian Computation and Model Selection S98

STAT461: Bayesian Nonparametric Regression F00

STAT7640: Bayesian Data Analysis S12, S14, S18

STAT8100: Topic courses: Statistics for Finance S14, S16

STAT8640: Bayesian Statistics I F00, F08, F10, F12, F16,F17

STAT9100: Recent Development of Statistics F10, F11

STAT9250: Monte Carlo and Statistical Computing S05, S18

STAT9640: Bayesian Statistics II: Advanced Theory S07, S09, S11, S13, S15, S17, S19

STAT9710: Mathematical Statistics I F07

STAT9720: Mathematical Statistics II S08, S19


Professional Membership

• Permanent member of American Statistical Association.

• Permanent member of Institute of Mathematical Statistics.

• Permanent member of International Chinese Statistical Association.

• Elected as an ordinary member of the International Statistical Institute.

Editorial Work

• Editor, Statistics and Related Fields, 2017-

• Associate Editor, Journal of the American Statistical Association, T&M, 2007–2013.

• Associate Editor, Communications in Statistics, 2006–2012.

• Associate Editor, Journal of Statistical Planning and Inference, 2012–2015.

• Co-Editor, Sankhya, Series B, 2008–2012.

• Editorial Board Member of International Journal of Statistics & Systems

(IJSS, http://www.ripublication.com/ijss.htm), 2006–.

Research Interests:

Bayesian methodology, survey sampling, small area estimation,

decision theory, business and econometrics,

survival analysis, reliability, space-time and longitudinal models,

generalized linear mixed models, fishery and wildlife conservation,

statistical computation, smoothing splines and nonparametric statistics.

Organizing and Program Committee of International Meetings

1. Co-chair of AMS-IMS-SIAM Summer Conference in Statistics, “Bayes, frequentist and likelihood

approaches to inference: a synthesis,” Mt. Holyoke College, MA, July 8-13, 2000.

2. Program Committee of The Third International Workshop on Objective Bayesian Methods, Ix-

tapa, Mexico, September 21-23, 2000.

3. Program Committee of The International Workshop on Objective Bayesian Methods, Granada,

Spain, December 6-8, 2002.

4. Program Committee of The Fourth International Workshop on Objective Bayesian Methods,

Aussois, France, June 15-20, 2003.

5. Chair of Organizers and Program Committee of The Fifth International Workshop on Objective

Bayesian Methods, Branson, USA, June 4-9, 2005.

6. Program Committee of the Sixth International Workshop on Objective Bayesian Methods, Rome,

Italy, June 5-9, 2007.

7. Program Committee of the International Indian Statistical Association (IISA) Conference, Fron-

tiers of Probability and Statistical Science, University of Connecticut-Storrs, May 22-25, 2008.

8. Program Committee of the International Workshop on Objective Bayesian Methods, University

of Pennsylvania, Philadelphia, June 5-9, 2009.

9. One of the 4 leaders in 2009-10 SAMSI Program on Space-time Analysis for Environmental

Mapping, Epidemiology and Climate Change.

10. Chair of Program Committee of of International Conference of Frontier of Statistical Decision

Theory, Universit of Taxes–San Antonio, March 16-18, 2010.

11. Chair of Organizers and Program Committee of The 2011 International Workshop on Objective

Bayesian Methods, East China Normal University, Shanghai, China, June, 2011.


12. Chair of Organizers and Program Committee of The 2013 International Workshop on Model

Selection, East China Normal University, Shanghai, China, January, 2013.

13. Co-Chair of Organizers and Program Committee of “Frontiers in Methodological and Applied

Statistics: A Celebration of 50 Years of Department of Statistics, University of Missouri, Septem-

ber 19-21, 2013.”

14. One of the Organizers and Program Committee of The 2013 International Workshop on Objective

Bayesian Methods, Duke University, December, 2013.

15. Chair of Organizers and Program Committee of The 2014 International Workshop on Adjusting

for Multiplicity, Shanghai, China, June 8-12, 2014.

16. Chair of Organizers and Program Committee of The First International Workshop on Bayesian,

Fiducial, and Frequentist Inference and Statistical Foundations, November10-14, 2014, Shanghai,

China.

17. Chair of Organizers and Program Committee of The Second International Workshop on Bayesian,

Fiducial, and Frequentist Inference and Statistical Foundations, 5-6, 2015, Shanghai, China.

18. One of the Organizers and Program Committee of The 2017 International Workshop on Objective

Bayesian Methods, University of Texas-Austin, December 9-13, 2017.

19. Chair of Organizing Committee, and Chair of Program Committee of SAE2018: Small Area

Estimation and Other Topics of Current Interest in Survey, Official Statistics, and General

Statistics, Shanghai, China, June 15-18, 2018.

Panels and External Review

1. NSF Panel, Research Equipment in NSF, December, 1999.

2. NSF Panel, BioComplexty Program, June 13-16, 2000.

3. NSF Panel, Program of Statistics and Probability, Jan 8-12, 2007.



6. NIH, Center for Scientific Review Special Emphasis Panel, July 13-14, 2009.

7. Member of the program review team for the Department of Statistics at Purdue University, April

4-6, 2004.

8. Chair of the program review team for the Department of Mathematics and Statistics at the

South Dakota State University, March 6-7, 2008.

9. Tenure reviews for Purdue University (four times), Taxes A&M University, University of Virginia,

University of New Hamsphire, Seol National University.

Mentoring Activity

Former Masters Students (Year Graduated, Thesis or Project Title)

1. Duo Zhou (2000). Bayesian Analysis of Response Time Data.

2. Robert Feyerham (2003). Bias in Parameter Estimates for Time Series AR Models. dual mastersin Statistics and Economics

3. Gentry White (2003). Implementing Bayesian Hierarchical Models Using WinBUGs.

4. Jun Lu, (2003). Bayesian Analysis for Response Time Learning.

5. DoYeun Park (2004). Forecasting Korean Exchange Rate Volatility, dual masters in Statisticsand Economics

6. Song Zhang (2004). Bayesian Semiparametric Models for Colorectal Cancer Incidence.

7. Joel Miller (2005). Dual masters in Statistics and Economics. Bayesian Time Series ModelSelection with Applications in the Derivation of Asset Prices.


8. Luyan Dai (2005). Bayesian Smoothing of Density Estimation via Hazard Rates.

9. Xiaoyan Lin (2005). Exploring a General Definition of Two-dimension Reference Priors.

10. Jillian Lane (2005). Bayesian Analysis of Trends in Response Waves.

11. Ke Na (2007). Bayesian Hierarchical Models for Multiple Beer Purchase Data, dual masters inStatistics and Economics

12. Jereme Shryock (May, 2009). A Structural Model of the United States Corn Industry: AnEconometric Investigation.

13. Ye Liang (May, 2009). Multivariate Conditional Autoregressive Modeling for Quality of Life inBreast Cancer Research.

14. Chester L. Schmaltz (May, 2009). Estimation of Hunting Success Rates, Hunter Pressure, andHarvest from Missouri’s Spring Turkey Hunter Surveys Using OpenBUGS.

15. Chang Xu (May, 2009). Bayesian Methods of Estimating Population Size Under Type II Cen-soring.

16. Yajun Liu (May, 2009). Hierarchical Bayes Models for QOL in Survivors of Breast Cancer .

17. Xiaoyi Min (May, 2010). Bayesian Model Selection for an m-way ANOVA Model.

18. Doug Lahmann (August, 2010). dual masters in Statistics and Economics.

Former PhD Students (Year Graduated, Dissertation Title, Current Position)

1. Gunhee Lee (Co-advisor: A.P. Basu) (1996). Noninformative Priors for Some Models Useful inReliability and Survival Analysis. Professor, Sogang University, Korea.

2. Seong-Wook Kim (1997). Bayesian Model Selection Using Intrinsic Priors for Commonly UsedModels in Reliability and Survival Analysis. Professor, Department of Applied Mathematics,Hanyang University, Korea. http://amath.hanyang.ac.kr/page/?pid=faculty

3. Hoon Kim (1999). Bayesian Hierarchical Spatio-Temporal Analysis of Mortality Rates withDisease Mapping. Professor of mathematics, California State Polytechnic University, Pomona.

4. Roger Woodard (1999). Bayesian Hierarchical Models for Hunting Success Rates. Professor ofStatistics, University of Notre Dame. The Inaugural Director of online MS-ACMS Data ScienceGraduate Program. USA.

5. John Molitor (1999). Bayesian Analysis for Various Order Restricted Problems.Associate Professor of Public Health, Oregon State University.

6. Yolande Tra (2000). Bayesian Analysis for Avian Nest Survival Models. Tenure-track assistantprofessor of statistics, Department of Math & Statistics, Rochester Institute of Technology.

7. Cuirong Ren (2001). Topics in Bayesian Estimation: Frequentist Risks and Hierarchical Mod-els for Time to Pregnancy. Associate Professor of Statistics, Feitian College at Middletown,NewYork.

8. Jake Oleson (Advisor; Co-advisor: C.Z. He) (2002). Bayesian Spatial Models for Small AreaEstimation. Professor of Biostatistics, Director of Graduate Study, University of Iowa. (Winnerof 2002 Donald K Anderson Graduate Research Assistant Award, Graduate School, UMC.)

9. Xiaoyin Wang (Advisor; Co-advisor: C.Z. He) (2002). Bayesian Analysis of Capture-RecaptureModels. Tenured associate professor of mathematics, in Division of Mathematics at TowsonUniversity, Maryland.

10. Suhwon Lee (Co-advisor; Advisor: P.L. Speckman) (2003). Nonparametric BayesianDensityEstimation with Intrinsic Autoregressive Priors. Teaching associate professor of statistics, Uni-versity of Missouri-Columbia.

11. Jun Lu (Advisor; Co-advisor: P.L. Speckman) (2004). Bayesian Hierarchical Models And Appli-cations In Psychology Research. Tenured associate professor of statistics, American University.

12. Song Zhang (2005). Bayesian Hierarchical Models and Applications in Cancer Analysis. Tenuredassociate professor of biostatistics, University of Texas Southwestern Medical Center.


13. Antonello Loddo (2006). Bayesian Analysis of Multivariate Stochastic Volatility and DynamicModels. Research statistician at Capital One.

14. Gentry White (Advisor; Co-advisor: P.L. Speckman) (2006). Bayesian Semiparametric FullySmoothed Spatio-Temporal Modelling. Senior Lecturer, Mathematical and Statistical SciencesSchool, Queensland University of Technology, Brisbane, QLD, 4001, Australia.

15. Mi Hyun Lee (2007, Virginia Tech). On Independent Reference Priors. Samsung ResearchInstitute of Finance.

16. Zhonggai Li (2008, Virginia Tech). Objective Bayesian Analysis of Kullback-Leibler Divergence oftwo Multivariate Normal Distributions with Common Covariance Matrix and Star-shape Gaus-sian Graphical Model. Novartis Pharmaceuticals Corporation.

17. Xiaoyan (Iris) Lin (2008). Bayesian Hierarchical Models for the Recognition-Memory Experi-ment. Tenure-track assistant professor of statistics, University of South Carolina.

18. Luyan Dai (2008). Topics in Objective Bayesian Methodology and Spatial-Temporal Models.Seninor Statisticians at Pfizer.

19. Sherry Gao (2010), Bayesian Spatial Models for Adjusting Nonresponse in Small Area Estima-tion. Biometrician, Missouri Department of Conservation.

20. Chester Lee Schmaltz (2012). Marginally Modeling Misaligned Regions and HandinG MaskedFailure Causes with Imprecision. Bio-Statistician, Medical School, University of Missouri.

21. Ye Liang (2012). Bayesian Methods on Selected Topics. Associate Professor of Statistics, Okla-homa Stat University.

22. Yajun Liu (2012). Bayesian Analysis of Spatial and Survival Models with Applications of Com-putation Techniques. Senior Statistians, Wells Fargo, NC, USA.

23. Chang Xu (2012). Estimating Population Size with Objective Bayesian Methods. Aiagen Sci-ences, Frederick, Maryland.

24. Xiaoyi Min (2012). Objective Bayesian Inference for ANOVA Models. Tenure-track assistantprofessor at Georgia State University.

25. Tri Minh Le (2014). The Formal Definition of Reference Priors Under A General Class OfDivergence, Tenure-track Assistant Professor of Mathematics and Computer Science, MercerUniversity, Atlanta, Georgia.

26. Xiaojun Tong (2015). Bayesian Smoothing Spline Models and their Application in EstimatingYield Curves, senior Statistian at People’s Bank of China.

27. Sifan Liu (2015). Partially Informative Normal and Partial Spine Models. Assistant Professor,Tianjin Institute of Finance.

28. Cheng Dong (2017). Some Topics in Multi-regional Clinical Trials and Meta-Analysis UsingBayesian Models.

29. Yuanyuan Bian (2018). Full Bayesian Models for Paired RNA-SEQ Data and Bayesian Equiv-alence Test.

30. Jiang Du (2018). Bayesian Hierarchical Modeling of Colorectal and Breast Cancer Data inMissouri.

31. John Snyder (2018). Objective Bayesian Analysis of the 2x2 Contingent Table and the NegativeBinomial Distribution.

32. Chetkar Jha (2019). A General Expression of Conditional Reference Prior.

Current PhD Students

33. Bengqian Zhang, since Fall, 2015, expected to complete in May of 2020;

34. WangYang Wang, since Fall, 2016; expected to complete in May of 2020;

35. Peng Shao, since Fall, 2016, expected to complete in May of 2020;

36. Qiao Wang, since Fall 2017;

37. Jiayi Hou, since Fall, 2018.


Post-Doctoral Fellow

1. Dr. Jaeyong Lee, (Jointly with Dr. Paul Speckman), at National Institute of Statistics Sciences,working Bayesian analysis for multinomial choice models.

2. Dr. Xiaoqian Sun (2002–2004). “Frequentist Properties of Bayesian Estimators of MultivariateCovariance Matrix.” Tenure-track assist. prof., Clemson University, South Carolina.

Having Served on Graduate Committees

1. Ms. Mary G. Richardson 1993 M. A. Statistics committee2. Ms. Janaki Kuruppu 1993 M. A. Statistics committee3. Ms. Yiqun Li 1997 M. A. Statistics committee3. Ms. Jing Cao 2003 M. A. Statistics committee

3. Ms. Yun Bao 2005 M. A. Statistics committee

4. Mr. Anura Abeyratne 1996 Ph.D. Statistics committee5. Mr. Kuo-Chin Lin 1996 Ph.D. Statistics committee6. Ms. Diann Reischman 1997 Ph.D. Statistics committee7. Ms. Suhwon Lee 2003 Ph.D. Statistics committee8. Mr. Ke Xu 2004 Ph.D. Statistics committee9. Ms Jing Cao 2005 Ph.D. Statistics committee10. Ms Ruixing Guo 2009 Ph.D. Statistics committee

10. Ms Zhang Jing 2009 Ph.D. Statistics committee

1. Mr. A. Gopalaratnam 1992 M. S. Computer Sciences outside reader2. Ms. Ling-Fen Chen 1993 M. S. Computer Sciences outside reader3. Mr. Ming-Fang Lee 1994 M. S. Computer Sciences outside reader4. Ms. Mei-hua Huang 1994 M. S. Computer Sciences outside reader5. Mr. Guoming Xue 1994 M. S. Civil Engineering outside reader6. Mr. Huaizhi Li 1996 M. S. Computer Sciences outside reader7. Ms. Yiqun Li 1997 M. A. Computer Sciences outside reader8. Mr. Zhiqin Wu 1997 M. S. Elec. Engineering outside reader9. Mr. John A. Zacher 1998 M. S. Civil Engineering outside reader10. Mr. Vandana Mehta 2003 M. S. Elec. Engineering outside reader

11. Mr. Unal Ufaktepe 1996 Ph.D. Mathematics outside reader12. Ms. Simona Stan 2000 Ph.D. Marketing outside reader

External Projects and Grants

Completed External Grants

E-1. 8/1/1995–7/31/1997: Co-PI. (PI.: P.L. Speckman), Statistics Research Computing Equipment.An NSF-SCREMS computing equipment grant, $60,812.

E-2. 1/1/1996–6/30/1997: PI. Investigations in Bayesian Analysis, Simulation and Development ofNoninformative Priors. National Security Agency, $15,000.

E-3. 7/1/1996–6/30/1999: PI., Bayesian Analysis for Nest Success Models. Missouri Department ofConservation,

E-4. 7/1/1996–6/30/1999: Co-PI (PI.: P.L. Speckman), Generating Activity Travel Patterns forSynthetic Populations. National Institute of Statistical Sciences, $153,418.

E-5. 07/01/1997–06/30/2004: PI. (CoPI: C.Z. He), Hierarchical Bayes Estimation of Small AreaEstimation for Harvest Surveys. Missouri Department of Conservation, direct cost of $155,678.


E-6. 8/1/1999–6/30/2003: PI. (CoPI.: P.L. Speckman), Bayesian Nonparametric Regression andDensity Estimation using CAR Priors. National Science Foundation (DMS-9972598), $127,750.

E-7. 07/01/2000–06/30/2004: CoPI. (PI: C.Z. He), Bayesian Estimation of Nest Survival Rates. Mis-souri Department of Conservation, direct cost of $80,848.

E-8. 07/01/2001–06/30/2004: PI. (CoPI: C.Z. He), Bayesian Analysis for Capture and RecaptureModels. Missouri Department of Conservation, direct cost of $70,298.

E-9. 03/15/2001–03/28/2005: CoPI. (PI: J.N. Rouder; Co-PI: P.L. Speckman), National ScienceFoundation (SES-0095919), A Parametric, Hierarchical Statistical Framework for Inference withSkewed Distributions, $299,998. One month/year for each of three CoPIs plus a 50% RA support.

E-10. 07/01/2003–06/30/2005, CoPI (PI: Francis Cheung; CoPI: Shawn Ni). Government Land Saleand Housing Market. Hong Kong Research Council Earmarked Grant, HK$249,000.

E-11. 07/01/2003–06/30/2005: CoPI (PI: M. Schootman, Washington University) GIS and BreastCancer Screening in Saint Louis. National Cancer Institute of NIH (R21 CA98594-01); Totalfunding, $280,000; portion at University of Missouri: $46,322: one month/year.

E-12. 08/01/2004-08/31/2005: CoPI (PI: C. Z. He). National Science Foundation (DMS-0439641).Conference in the Mathematical Sciences on New Developments of Statistical Analysis in Wildlife,Fisheries, and Ecological Research, $20,000.

E-13. 06/01/2005-05/30/2006: PI: National Security Agency (H98B230-05-1-0272). The Fifth Interna-tional Workshop on Objective Bayesian Methodology in Branson, MO, June 4-8, 2005. $14,900.

E-14. 06/01/2005-05/30/2006: PI: (CoPI: P.L. Speckman). National Science Foundation (DMS-0506743).The Fifth International Workshop on Objective Bayesian Methodology in Branson, MO, June 4-8,2005. $12,000.

E-15. 12/01/2004-11/30/2006: NIDDK (National Institute of Dibetes and Diggestive and Kidney Dis-eases) of NIH (R21 DK067172), Co-PI (PI: M. Schootman, Washington University); Geographyof Amputations Among African Americans. Total funding, $280,000; portion at University ofMissouri: $75,000, 1 month/year plus a 25% RA support.

E-16. 09/01/2004-05/30/2007: National Cancer Institute of NIH (R01 CA100760); CoPI (PI: M.Schootman, Washington University). PI of subcontract. Geographic Variation of Breast CancerSurvival. Total funding: $808,175; portion at University of Missouri: $291,000; 2 months/yearfor D. Sun, 1 month/year for C.Z. He, plus a 50% RA support.

E-17. 06/01/2004–05/31/2008: CoPI. (PI: P.L. Speckman, Co-PI: J.N. Rouder), National Science Foun-dation (SES-0351523), Bayesian Hierarchical Models for Inference with Behavior Data. $299,999,1 month/year for each of three CoPIs plus a 50% RA support.

E-18. 07/01/2004–06/30/2008: PI. (CoPI: C.Z. He), Adjusting Nonresponse Biases for Attitude Sur-veys. Missouri Department of Conservation, direct cost of $166,088 plus tuition and indirectcost.

E-19. 06/01/2005-05/30/2009: CoPI. (PI: J.N. Rouder, Co-PI: P.L. Speckman), Bayesian HierarchicalModels for Psychological Research. National Institute of Mental Health/NIH, (R01 MH071418).$638,739, direct cost of $150,000 per year; 2 months/year for each of three CoPIs plus two 50%RAs.

E-20. 07/01/2005–06/30/2009: PI. WinBUGs Application in Hunting Survey. Missouri Department ofConservation, direct cost of $104,100 plus tuition and indirect cost.

E-21. 09/15/2007-08/14/2010: PI (Co-PIs: J.N. Rouder and P.L. Speckman), National Science Foun-dation (SES-0720229), Bayesian Models for Assessing Shape and Covariance in Behavioral Data.$290,000.

E-22. 07/01/2006-06/30/2010: National Cancer Institute of NIH (R01 CA112159); PI of subcontract(PI: M. Schootman, Washington University); Neighborhood Effects on Quality of Life in BreastCancer. Total funding, $1,219,000. portion at University of Missouri: $297,629.


E-23. 07/01/2008-08/31/2011: National Cancer Institute of NIH (R01 CA109675); Spatial, Temporal,Social Disparities in Breast Cancer. Total requestd, $1,100,000. PI of subcontract (PI: M.Schootman, Washington University); portion at University of Missouri: $200,300.

E-24. 07/01/2007-06/30/2012: NIG NIGMS, Co-PI (PI: Jiangguo Sun). Predoctoral Research Trainingin Biostatistics at the University of Missouri-Columbia. Total funding, $331,035.

E-25. 07/01/2009-02/28/2014: National Cancer Institute of NIH (R01 CA137750); PI of subcontract(PI: M. Schootman, Washington University); Co-PI: Chong Z. He, Geographic Disparties inColorectal Cancer Survival. portion at MU: $77,209.

E-26. 06/01/2010-05/31/2015: PI. National Science Foundation (DMS-1007874), Collaborative Re-search: Bayesian Anaylsis and Applicstions. $150,000.

E-27. 10/01/2010-09/30/2013: PI (Co-PIs: J.N. Rouder and P.L. Speckman), National Science Founda-tion (SES-1024080), Bayesian Methodology for Assessing Invariance in Behavioral Data. $340,000.

E-28. 04/01/2013-06/31/2015: PI (Co-PIs: J.N. Rouder and P.L. Speckman), National Science Foun-dation (SES-1260806), Bayes Factor Methods for Model Comparison in the Social Sciences,$150,000.

E-29. 09/01/2018–08/31/2019: Visiting Research Fellows in Modeling Uncertainty: Mathematical andStatistical (MUMS) Program at SAMSI. Portion at University of Missouri: $48,502.

Active External Grants

E-30. 04/01/2016–03/31/2021: (Investigator, PI: Chi-Ren Shyu). National Institute of Health 1T32LM012410-01, Massive and complex data analytics pre-doctoral training in one health, $1,486,000,

E-31. 01/01/2003–: PI. Statistics Analysis of Cancer Incidence and Mortality. Missouri Cancer Reg-istry, MS. Qiao Wang is currently under supported with a stipend of $26,000 annually plus tuitionand fee waiver.

Internal Projects and GrantsCompleted Grants from University of Missouri-System

I-1. 6/1/1993-6/30/1994: PI., On Bayesian Optimal Design. $11,000.

I-2. 6/1/1996–6/30/1997: Co-PI. (PI.: Robert K. Tsutakawa). Geographic and Longitudinal Analysisof Mortality Rates. $19,541.

I-3. 3/1/2002-2/28/2003: PI, (Co-PI, Shawn Ni of Economics). Bayesian Analysis of Vector-AutoregressiveModels. $20,196.

Completed Grants from University of Missouri-Columbia (UMC)

I-4. 1994: PI., Methodology of Noninformative Priors and Computation. Summer Research Fellowshipof $4,000 and Research Council grant of $2,650.

I-5. 1995: PI., Applications of Noninformative Priors. Summer Research Fellowship of $4,000 andResearch Council grant of $3,000.

I-6. 1997: PI., Bayesian Analysis Under Partial Prior Information. Summer Research Fellowship of$7,000 and Research Council grant of $3,000.

I-7. 07/2003-06/2004: PI. Objective Bayesian Analysis. Research Council grant of $5,000.

Faculty International Travel Grants from UMC

I-8. 06/01–06/07/1994: PI. To present and attend the Fifth Valencia International Meeting of theInternational Society for Bayesian Analysis. $900, Spain.

I-9. 05/29–06/04/1996: PI. To present and attend the ISBA 1996: Fourth World Meeting of theInternational Society for Bayesian Analysis. $1,000. Hersonissos, Crete.


I-10. 05/30–06/04/1998: PI. To present and attend the Sixth Valencia International Bayesian Meeting.Alcossebre, Spain. $1,192.

I-11. 05/28–06/04/2000: PI. To present and attend ISBA 2000: Sixth World Meeting of the Interna-tional Society for Bayesian Analysis. Hersonissos, Crete. $1,187.

I-12. 06/01–06/06/2002: PI. To present and attend the Seventh Valencia International BayesianMeeting. at Valencia, Spain. $1,369.

I-13. 05/22–05/28/2004: PI. To present and attend International Society for Bayesian Analysis (ISBA)2004 World Meeting at Vina del Mar, Chile. $1,500.

Refereed Articles

[1] Zhou, J.X. and Sun, D. (1984). Some problems on testing position and scale parameters togetherin a growth curve model. J. of East China Normal University, Natural Science Ed., No. 2, 20-26.

[2] Sun, D. (1985). Strongly consistent double kernel estimators of conditional density. Chinese J.of Applied Probability and Statistics, 1, 481-486.

[3] Sun, D. (1985). The asymptotic normality of linear functions of conditional order statistics. ActaMathematica Sinica, English Ed. 2, 33-56.

[4] Sun, D. (1985). Mean square error for uniform-kernel estimate and nearest neighbor estimate ofnonparametric regression functions. Acta Mathematica Scientia, English Ed. 5, 175-185.

[5] Sun, D. (1986). The strong consistency of nonparametric regression based on concomitants oforder statistics. Acta Mathematicae Applicatae Sinica, 10, 352-359.

[6] Sun, D. (1986). Strong consistency of kernel estimates of regression functions. Chinese Annalsof Mathematics, Series A, 6, 481-486.

[7] Sun, D. (1986). Consistent random window size kernel estimators of regression functions. ActaMathematicae Applicatae Sinica, 9, 215-221.

[8] Zhang, B. and Sun, D. (1986). Methods of determining environment factors for Weibull variables.J. of Chinese Society of Astronautics, 72-80.

[9] Wang, J. and Sun, D. (1986). Admissible estimators in the one-parametric exponential family.Chinese J. of Applied Probability and Statistics, 2, 120-127.

[10] Sun, D. (1987). A law of the iterated logarithm for nonparametric conditional density estimators.Acta Mathematica Scientia, (English Ed.) 7, 159-167.

[11] Sun, D. (1987). Mean square errors for uniform kernel estimates and nearest neighbor estimatesof probability density functions. J. Math. Research & Exposition, 7, 301-304.

[12] Sun, D. (1987). Necessary conditions of L1-convergence of kernel regression estimators. ChineseAnnals of Mathematics, Series B (English Ed.) 8, 410-419.

[13] Berger, J.O. and Sun, D. (1993). Bayesian analysis for the poly-Weibull distribution. Journal ofthe American Statistical Association, 88, 1412-1418.

[14] Sun, D. (1994). Integrable expansions for posterior distributions for a two-parameter exponentialfamily. Annals of Statistics, 22, 1808-1830.

[15] Sun, D. and Berger, J.O. (1994). Bayesian sequential reliability for Weibull and related distribu-tions. Annals of the Institute of Statistical Mathematics, 46, 221-249.

[16] Sun, D. and Ye, K. (1995). Reference prior Bayesian analysis for normal mean products. Journalof the American Statistical Association, 90. 589-597.

[17] Gupta, S., Miao, B. and Sun, D. (1995). A two-stage procedure for selecting the population withthe largest mean when the common variance is unknown. Chinese Journal of Applied Probabilityand Statistics, 11, 113-127.

[18] Sun, D. Tsutakawa, R.K. and Lu, W. (1996). Bayesian design of experiment for quantal responses:what’s promised versus what’s delivered. Journal of Statistical Planning and Inference, 52, 289-306.


[19] He, Z., Studden, W.J, and Sun, D. (1996). Optimal designs for rational models. Annals ofStatistics, 24, 2128-2137.

[20] Sun, D. and Ye, K. (1996). Frequentist validity of posterior quantiles for a two-parameter expo-nential family. Biometrika, 83, 55-65.

[21] Sun, D. and Tsutakawa, R.K. (1997). Bayesian design for dose responses with extra penalty forunexpected outcomes. Biometrics, 53, 1262-1273.

[22] Clarke, B.S. and Sun, D. (1997). Reference priors under the chi-square distance. Sankhya A., 59,215-231.

[23] Sun, D. (1997). A note on noninformative priors for Weibull distributions. Journal of StatisticalPlanning and Inference, 61, 319-338.

[24] He, C.Z. and Sun, D. (1998). Hierarchical Bayes estimation of hunting success rates. Environ-mental and Ecological Statistics, 5, 223-236.

[25] Sun, D., Ghosh, M. and Basu, A.P. (1998). Bayesian analysis for a stress-strength system vianoninformative priors. Canadian Journal of Statistics, 26, 323-332.

[26] Sun, D. (1998). On exact computations for sequential tests for a class of exponential distributions.Sequential Analysis, 17, 127-150.

[27] Sun, D. and Berger, J.O. (1998). Reference priors under partial information. Biometrika, 85,No. 1, 55-71.

[28] Sun, Y., Hobbs, D., Elder, W. and Sun, D. (1998). Parental involvement–a contrast betweenrural and other communities. Southern Rural Sociology, 13, 41-64.

[29] Sun, D. and Ye, K. (1999). Reference priors for a product of normal means when variances areunknown. Canadian Journal of Statistics, 27, 97-103.

[30] Sun, D., Tsutakawa, R.K. and Speckman, P.L. (1999). Posterior distribution of hierarchicalmodels using CAR (1) distributions. Biometrika, 86, 341-350.

[31] Woodard, R., Sun, D. He, C.Z. and Sheriff, S.L. (1999). Estimating hunting success rates viaBayesian generalized linear models. Journal of Agricultural, Biological and Environmental Statis-tics, 4, 456-472.

[32] Clarke, B.S. and Sun, D. (1999). Asymptotics of the expected posterior. Annals of the Instituteof Statistical Mathematics, 51, 165-185.

[33] Sun, D., Tsutakawa, R.K., Kim, H. and He, C.Z. (2000). Spatio-time interaction with diseasemapping. Statistics in Medicine, Vol 19, No. 15, 2015-2035.

[34] Kim, S.W. and Sun, D. (2000). Intrinsic priors for model selection using an encompassing model.Lifetime Data Analysis, 6, 251-269.

[35] He, C.Z. and Sun, D. (2000). Hierarchical Bayes estimation of hunting success rates with spatialcorrelations. Biometrics, 56, 360-367.

[36] Kim, H., Sun, D., and Tsutakawa, R.K. (2001). Bivariate Bayesian methods for improving esti-mators of mortality rates with 2-fold CAR model. Journal of the American Statistical Association,96, 1506-1521.

[37] He, C.Z., Sun, D., and Tra, Y. (2001), Bayesian analysis for bird nest survival models, Biometrics,57, 1059-1066.

[38] Sun, D., Tsutakawa, R.K., and He, C.Z. (2001). Propriety of posteriors with improper priors inhierarchical linear mixed models. Statistica Sinica, 11, 77-95.

[39] Kim, H., Sun, D., and Tsutakawa, R.K. (2002). Lognormal vs. Gamma: extra variations.Biometrical Journal, 44, 305-323.

[40] Molitor, J. and Sun, D. (2002). Bayesian analysis of problems involving ordering of functions ofparameters. Environmental and Ecological Statistics, 9, 179-193.


[41] Woodard, R., He, C.Z. and Sun, D. (2003). Bayesian estimation of hunting success rate andharvest for spatially correlated post-stratified data. Biometrical Journal, 45, 985-1005.

[42] Speckman, P.L. and Sun, D. (2003). Full Bayesian spline smoothing and intrinsic autogressivepriors. Biometrika, 90, 289-302.

[43] Ni, S. and Sun, D. (2003). Frequentist risks of Bayesian estimators of vector-autoregressive modelsbased on noninformative priors. Journal of Econometrics, 115, 159-197.

[44] Rouder, J.N., Sun, D., Speckman, P.L., Lu, J. and Zhou, D. (2004). A hierarchical Bayesianstatistical framework for skewed variables with an application to response time distributions, Psy-chometrika, 68, 589-606.

[45] Sun, D. and Ni, S. (2004). Bayesian analysis of vector-autoregressive models with noninformativepriors. Journal of Statistical Planning and Inference, 121, 291-309.

[46] Schootman, M. and Sun, D. (2004). Estimation of the variability of small-area breast cancerincidents trends, Epidemiology, 15, 300-307.

[47] Ren, C., Sun, D., and Dey, D. (2004). Comparison of Bayesian and frequentist estimation andprediction for normal population. Sankhya, 66, 678-706.

[48] Wang, X., He, C.Z., and Sun, D. (2005). Bayesian inference on the patient population size givenlist mismatches. Statistics in Medicine, 24, 249-267.

[49] Zhang, S., Sun, D., and Chanetsa, F. (2005). Spatial-Temporal Trend of Smoking Rates in MissouriDuring 1990–2001. Far East Journal of Theoretical Statistics, 16, 69-85.

[50] Sun, X. and Sun, D. (2005). Estimation of the Cholesky decomposition of the covariance matrixin the star-shape model. Statistics and Probability Letter, 73, 1-12.

[51] Ni, S. and Sun, D. (2005). Alternative Bayesian estimators for vector-autoregressive models.Journal of Business and Economic Statistics, 23, 105-117.

[52] Rouder, J., Lu, J., Speckman, P.L., Sun, D., and Jiang, Y. (2005). A hierarchical model forestimating response time distributions. Psychonomic Bulletin and Review, 12, 195-223.

[53] Sun, D. and Speckman, P.L. (2005). A note on existence of posterior moments. Canadian Journalof Statistics, 33, 591-601.

[54] Ren, C., Sun, D., Speckman, P.L., He, C.Z. and Swan, S. (2005). Hierarchical models for theprobabilities of conception. Biometrical Journal, 47, 721-739.

[55] Sun, D. and Sun, X. (2005). Estimation of multivariate normal precision and covariance matricesin a star-shaped model. Annals of the Institute of Statistical Mathematics, 57, 455-484.

[56] Sun, D. and Sun, X. (2006). Estimation of the normal precision matrix and covariance matrixwith missing data. Journal of Multivariate Analysis, 97, 698-719.

[57] Zhang, S., Sun, D., He, C.Z., and Schootman, M. (2006). A Bayesian semiparametric model forcolorectal cancer incidence. Statistics in Medicine, 25, 285-309.

[58] Ren, C., Sun, D., and Dey, D. (2006). Bayesian and frequentist estimation and prediction forexponential distributions. Journal of Statistical Planning and Inference, 136, 2873-2897.

[59] White, G. and Sun, D. (2006). Simultaneous estimation of hunting pressure, harvest and huntersuccess rates using WinBUGs. Far East Journal of Theoretical Statistics, 18, 91 - 116.

[60] Dai, L. He, C., Sun, D. and Schootman, M. (2007). Hierarchical models for detecting multi-levelgeographical effects in cancer incidence and survival. Far East Journal of Applied Mathematics,29, 1-18.

[61] Wang, X., He, C.Z., and Sun, D. (2007). Bayesian population estimation for a capture-recapturemodel using non-informative priors. Journal of Statistical Planning and Inference, 137, 1099-1118.

[62] White, G., Sun, D., and Schootman, M. (2007). An additive model for spatio-temporal smoothingof cancer mortality rates. Iranian Journal of Mathematical Sciences and Informatics, 2, 57-72.


[63] Sun, X. and Sun, D. (2007). Estimation of the multivariate normal covariance matrix withstaircase pattern data. Annals of the Institute of Statistical Mathematics, 59, 211-233.

[64] Sun, D. and Berger, J. O. (2007). Objective priors for the multivariate normal model. BayesianStatistics 8, with discussion, 525-564.

[65] Garcıa-Donato, G. and Sun, D. (2007). Consistency of objective Bayes factors for one-wayANOVA random effects models. Canadian Journal of Statistics, 35, 303-320.

[66] Gao, X, He, C.Z., and Sun, D. (2007). Hierarchical Bayes estimation of response rates for a deerhunter attitute survey with spatial correlation. Far East Journal of Mathematical Science, 26,715-732.

[67] Ni, S., Sun, D. and Sun, X. (2007). Bayesian analysis for vector-autoregressive models under theintrinsic loss. Journal of Business and Economic Statistics. 25, 163-176.

[68] Oleson, J., He, C. Z. and Sun, D. (2007). Bayesian estimation in small areas under pre-andpost-stratification. Survey Methodology, 33. 173-185.

[69] Rouder, J.N., Lu, J., Sun, D., Speckman, P.L., Morey, R.D. and Naveh-Benjamin, M. (2007).Signal detection models with random participant and item effects. Psychometrika, 72, 621-642.

[70] George, E., Sun, D., and Ni, S. (2008). Stochastic Search Model Selection for Restricted VARModels. Journal of Econometrics, 142, 553-580.

[71] Solari, F., Liseo, B., and Sun, D. (2008). Some remarks on Bayesian inference for one-way ANOVAmodels. Annals of the Institute of Statistical Mathematics, 60, 483-498.

[72] Sun, D. and Speckman, P. (2008). Bayesian hierarchical linear mixed models for additive smooth-ing splines. Annals of the Institute of Statistical Mathematics, 60, 499-517.

[73] Berger, J. O. and Sun, D. (2008). Objective priors for the bivariate normal model with multi-variate generalizations. The Annals of Statistics, 36, 963-982.

[74] Rouder, J. N., Lu, J., Morey, R. D., Speckman, P. L., and Sun, D. (2008). A hierarchical processdissociation model. Journal of Experimental Psychology: General, 137, 270-289.

[75] Berger, J.O., Bernardo, J., and Sun, D. (2009). The formal definition of reference priors. Annalsof Statistics, 37, 905-938.

[76] Berger, J. O., Bernardo, J. M. and Sun, D. (2009). Natural induction: An objective Bayesianapproach. Rev. Acad. Sci. Madrid, A 103, 125-159 (with discussion).

[77] Rouder, J.N., Speckman, P.L., Sun, D., Morey, R.D. and Iverson, G. (2009). Bayesian t tests foraccepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225-237.

[78] Speckman, P.L., Lee, J. and Sun, D. (2009). Existence of the MLE and propriety of posteriorsfor a general multinomial choice model. Statistica Sinica, 19, 731-748.

[79] Liseo, B., Solari, F., and Sun, D. (2009). Noninformative priors under special patterns of theFisher information matrix. Sankaya, 71-A, Part 2, 284-297.

[80] Lin, X. and Sun, D. (2010). A note on the existence of the posteriors for one-way random effectprobit models, Statistics and Probability Letter, 80, 57-62.

[81] Min, X. Sun, D., He, Z., and Schootman, M. (2010). Bayesian Hierarchical Model of NontraumaticLower-Extremity Amputation Rates. The Journal Spatial and Space-Time Epidemiology, Vol 1,169-176.

[82] Fokoua, E., Sun, D., and Goel, P. (2011). Fully Bayesian analysis of the relevance vector machinewith an extended hierarchical prior structure. Statistical Methodology, 8, 83-96.

[83] Loddo, A., Ni, S., and Sun, D. (2011). Bayesian Selection of Multivariate Stochastic VolatilityModels. Journal of Business and Economic Statistics. 29, 342-355.

[84] Yue, Y., Speckman, P., and Sun, D. (2012). Fully Bayesian adaptive spline smoothing, Annals ofthe Institute of Statistical Mathematics, 64, 577-613.


[85] Ren, C., Sun, D. and He, Z. (2012). Objective Bayesian Analysis for a Spatial Model with NuggetEffects, Journal of Statistical Planning and Inference, 142, 1933-1946.

[86] Berger, J.O., Bernardo, J., and Sun, D. (2012). Objective Priors for Discrete Parameter Spaces,Journal of the American Statistical Association, 107, 636-648.

[87] Liang, Y. and Sun, D. (2012). Objective Priors for Generative Star-shape Models. Statistics andProbability Letter, 82, 991-997.

[88] Wang, H. and Sun, D. (2012). Objective Bayesian Analysis for a Truncated Model. Statisticsand Probability Letter, 82, 2125-2135.

[89] Sun, D. and Ni, S. (2012). Bayesian Testing of Restrictions on Vector Autoregressive Models.Journal of Statistical Planning and Inference, 142, No. 11, 3008-3022.

[90] Min, Xiaoyi and Sun, D. (2013). Matching Priors Based on a Pseudo-Likelihood in Two WeibullStress-Strength Models. Canadian Journal of Statistics, 41, 83-97.

[91] Ren, C., Sun, D. and Sahu, S. (2013). Objective Bayesian analysis of spatial models with separablecorrelation functions, Canadian Journal of Statistics, 41, 488-507.

[92] Lin, X., Sun, D., Speckman, P.L. and Rouder, J. N. (2013). Existence of MLE and posteriors fora recognition-memory model. Statistics and Probability Letter, 83, 2415-2421.

[93] Ren, C. and Sun, D. (2013). Objective Bayesian Analysis for CAR Models. Annals of the Instituteof Statistical Mathematics, 65, 457-472.

[94] Sun, D. and Ni, S. (2014). A Bayesian Analysis of normalized VAR models. Journal of Multi-variate Analysis, 124, 247-259.

[95] Ren, C. and Sun, D. (2014). Objective Bayesian Analysis for Autoregressive Models with NuggetEffects. Journal of Multivariate Analysis, 124, 260-280.

[96] Liu, Yajun, Sun, D. and He, Z.C. (2014). A hierarchical CAR model for colorectal cancer survivaldata. Wiley Interdisciplinary Reviews: Computational Statistics, 6,, No. 1, 37-44.

[97] Liu, Yajun and Sun, D. (2014). Should we use ASIS? Chinese J. of Applied Probability andStatistics, 30,, No. 1, 1-11.

[98] Xu, Chang, Sun, D, and He, Z.C. (2014). Objective Bayesian Analysis for a Capture-recaptureModel. Annals of the Institute of Statistical Mathematics, 66, 245-278.

[99] Gao, S., He, Z.C., and Sun, D. (2014). A Bayesian Spatial Model with Auxiliary Covariates toAssess and Adjust Nonignorable Nonresponse. Spatial Statistics, 8, 122-144.

[100] Gao, S., He, Z.C., and Sun, D. (2014). Adjusting Nonresponse Bias in small area estimationwithout covariates via a Bayesian Model. Statistics and Its Interface, 7, 517-530.

[101] Liang, Y., Sun, D., He, Z.C, and Schootman, M. (2014). Modeling Bounded Outcome ScoresUsing the Bionomial-Logit-Normal Distribution. Chilean Journal of Statistics, 5, 3-14.

[102] Wang, X., He, Z.C., and Sun, D. (2015). Bayesian Estimation of Population Size via Capture-Recapture Model with Time Variation and Behavioral Response. Open Journal of Ecology, 5,1-13.

[103] Berger, J.O., Bernardo, J., and Sun, D. (2015). Overall Objective Priors. Discussion paper,Bayesian Analysis, 10, 189-221, Rejoinder, 243-246.

[104] Xu, Ancha., Tang, Yingcai, and Sun, Dongchu (2015). Objective Bayesian analysis for maskeddata under symmetric assumption. Statistics and Its Interface, 8, 227-237.

[105] Min, X. and Sun, D. (2016). Bayesian model selection for a linear model with grouped covariates.Annals of the Institute of Statistical Mathematics, 68, 877-903.

[106] Liang, Y. and Sun, D. (2016). Identifiability of masking probabilities in competing risks modelswith emphasis on Weibull models. Communication in Statistics, Theory and Method, 45, 2143-2157.


[107] Page, G. , Liu, Y., He, Z.C., and Sun, D. (2017). Estimation and prediction in the presence ofspatial confounding for spatial linear models. Scandinavian Journal of Statistics, 44, 581-616.

[108] Tong, X., He, Z.C., and Sun, D. (2018). Estimating Chinese treasury yield curves with Bayesiansmoothing spline. Econometrics and Statistics, Volumne 8, 94-124.

[109] Du, J. Sun, D., Schmaltz, C. L. , Jacson-Thompson, J. (2018). Using BRFSS data to estimatecounty-level colorectal cancer screening prevalence in Missouri. Epidemiology international journal.Volume 2, Issue 1.

[110] Sheriff, S.L, Sun, D., He, Z., Vangilder, L.D. and Isabelle, J.L. (2018). Model selection for wildturkey hunter success rates using small area estimation methods. Wildlife Society Bulletin, Vol42, No 2, 622-631.

[111] Wang, X., Berg, E., Zhu, Z. Sun, D. and Demuth, G. (2018). Small area estimation of proportionswith constraint for national resources inventory survey. Journal of Agricultural Biological andEnvironmental Statistics, 23, No. 4, 509-528.

[112] He, L., Sun, D., and He, Daojiang. (2019). Objective Bayesian analysis for accelerated degradationdata using inverse Gaussian process models. Statistics and Its Interface, 12, 295307.

[113] Berger, J.O., Sun, D., and Song, C. (2019). Bayesian Anaylsis of Covariance Matrix of Multivari-ate Normal Distribution with a New Class of Priors. Annals of Statistics, in press.

[114] Berger, J.O., Sun, D., and Song, C. (2019). An Objective Prior for Hyperparameters in NormalHierarchical Models. Journal of Multivariate Analysis, in press.

[115] He, Daojiang. Sun, D., and He, L. (2019). Objective Bayesian Analysis for the Student-t LinearRegression Model. Bayesian Analysis, in press.

[116] Song, C. and Sun, D. (2019). A Class of Admissible Estimators of Multiple Regression Coefficientwith an Unknown Variance. Statistical Theory and Related Fields, in press.

[117] Song, C., Bell, W.R., Berger, J.O., He, Z., and Sun, D.. (2019). Bayesian Analysis of MultivariateOne-Way ANOVA Model. Submitted.

[118] Song, C., Sun, D., Berger, J.O., and He, Z., (2019). Posterior Propriety and Admissibility ofBayesian Estimators for a 3-Level Normal Hierarchical Model. Submitted.

[119] Du, J. Sun, D., Schmaltz, C. L. , Jacson-Thompson, J. and He, C.Z. (2019). Jointly ModelingColorectal Cancer Incidence and Mortality Rates on Misaligned Regions in Missouri. Submitted.

[120] Wang, W. and Sun, D. (2019). An Enhanced AdaBoost Algorithm for Imbalance Data Classication.Submitted.

[121] Sun, D. and Ni, S. (2019). Objective Bayesian Analysis for AR(2) Models. Submitted.

[122] Sun, D. and Ni, S. (2019). Intrinsic Bayesian Estimators of Linear Time Series Models. Submitted.

Articles in Refereed Books

[123] Sun, D. and Berger, J.O. (1993). Recent developments in Bayesian sequential reliability demon-stration tests, in Advances in Reliability, ed. by Basu, A., North-Holland, Amsterdam, 379-394.

[124] Berger, J.O. and Sun, D. (1996). Bayesian inference for a class of poly-Weibull distributions, inBayesian Statistics and Econometrics, Donald A. Berry et al., eds., John Wiley, 101-114.

[125] Ghosh, M. and Sun, D. (1998). Recent developments of Bayesian inference for stress-strengthmodels. In the Indian Association for Productivity Quality and Reliability (IAPQR) volume titledFrontiers in Reliability, 143-158.

[126] Sun, D., Speckman, P.L., and Tsutakawa, R.K. (2000). Random effects in generalized linearmixed models (GLMMs). In Generalized Linear Models: A Bayesian Perspective, Dipak K. Dey,Bani K. Mallick and Sujit Ghosh, eds., Marcel Dekker Inc., 23-39.

[127] He, C.Z. and Sun, D. (2005). Bayesian survival analysis for discrete data with left-truncationand interval censoring. In Handbook of Statistics, Vol. 25 on Bayesian Statistics, D. Dey and C.R.Rao, eds., Elsevier, 913-934.


[128] Sun, D. and Berger, J.O. (2008). Objective priors under sequential experimentation. In IMSLecture Notes-Monograph Series. A special volume in honor of Dr. Jayanta K. Ghosh.

[129] Dai, Luyan and Sun, D. (2010). Exact Matching Inference for a Multivariate Normal Model. InFrontiers of Statistical Decision Making and Bayesian Analysis – in Honor of James O. Berger.Ming-Hui Chen, Dipak Dey, Peter Muller, Dongchu Sun and Keying Ye, eds., Springer, 237-246.

Refereed Articles in Conference Proceedings

[130] He, Z., Sun, D. and Tra, Y. (2000), Bayesian analysis for avian nesting survival models withdirichlet priors. Proceeding of International Society for Bayesian Analysis Sixth World Meeting,Crete, Greece, May 28-June 2, 2000.

[131] Sheriff, S.L., Sun, D., He, Z. and Woodard, R. (2001). Using Bayesian analysis for spatialestimation of turkey hunter success rates. In Bayesian Methods with Applications to Science,Policy and Official Statistics. Monographs of Official Statistics, EuroStat, European Communities,Luxembourg. Ed. by E. I. George, 497-506.

Non-refereed Articles in Conference Proceedings

[132] Sun, D. and Ye, Y. (1995). Frequentist validity of posterior quantiles. 1995 Proceedings of theSection on Bayesian Statistical Science, Alexandria: American Statistical Association, 127-131.

[133] Sun, D. and Ye, Y. (1995). Reference priors for normal mean products. 1995 Proceedings of theSection on Bayesian Statistical Science, Alexandria: American Statistical Association, 132-137.

[134] He, C.Z. and Sun, D. (1997). Bayesian estimation of hunting success rates of dependent data.1997 Proceedings of the Section on Biometrics, Alexandria: American Statistical Association, 112-117.

[135] He, C.Z., Sun, D. and Tra, Y. (1997). Bayesian analysis for avian nest survival models. 1997Proceedings of the Section on Bayesian Statistical Science, Alexandria: American Statistical As-sociation. 27-32.

[136] Kim, H., Sun, D. and Tsutakawa, R.K. (1999). A bivariate Bayes method with 2–fold CAR model,1999 Proceedings of the Section on Bayesian Statistical Science, Alexandria: American StatisticalAssociation.

[137] Speckman, P.L. and Sun, D. (1999). Bayesian nonparametric regression via conditional au-toregressive models, 1999 Proceedings of the Section on Bayesian Statistical Science, Alexandria:American Statistical Association.

[138] Wang, X., He, C.Z. and Sun, D. (2003). Batesian population estimate in epidemiology. 2003 Pro-ceedings of the American Statistical Association, Bayesian Statistical Science Section, Alexandria:American Statistical Association: 4440-4445.

[139] Lu, J., Sun, D., Speckman, P.L., and Rouder, J.N. (2004). Hierarchical models for learning effectsin response time. 2004 Proceedings of the Section on Bayesian Statistical Science, Alexandria:American Statistical Association.

[140] Gao, X, He, C.Z., and Sun, D. (2006). Hierarchical Bayes Estimation of Response Rates withSpatial Correlations. 2006 Proceedings of the American Statistical Association, Bayesian StatisticalScience Section, Alexandria: American Statistical Association: 33-40.

[141] Loddo, A., Ni, S., and Sun, D. (2006). Bayesian Selection of Multivariate Stochastic VolatilityModels. 2006 Proceedings of the American Statistical Association, Bayesian Statistical ScienceSection, Alexandria: American Statistical Association: 89-96.

[142] Ni, S. and Sun, D. (2006). Bayesian Analysis of Multivariate State-Space Models with Nonin-formative Priors. 2006 Proceedings of the American Statistical Association, Bayesian StatisticalScience Section, Alexandria: American Statistical Association: 109-114.


[143] Gao, X, Sun, D., and He, C.Z. (2007). Estimate response rate and satisfaction rates jointly viahierarchical Bayesian approach. 2007 Proceedings of the American Statistical Association, BayesianStatistical Science Section, Alexandria: American Statistical Association: 1273-1280.

[144] Lin, X. and Sun, D. (2007). Objective Bayesian Analysis in Memory Study. 2007 Proceedings ofthe American Statistical Association, Bayesian Statistical Science Section, Alexandria: AmericanStatistical Association: 1212-1219.

[145] Ni, S. and Sun, D. (2007). Reference Priors for AR(2) Models. 2007 Proceedings of the Ameri-can Statistical Association, Bayesian Statistical Science Section, Alexandria: American StatisticalAssociation: 1322-1328.

[146] Schmaltz, C. and Sun, D. (2010). Marginally Conditional Autoregressive Distributions for Mis-aligned Regions. 2010 Proceedings of the American Statistical Association, Section on BayesianStatistical Science. Alexandria, VA: American Statistical Association. 4984–4998.

Discussion Papers

[147] Sun, D. (1994). Comments on Professor Sweeting’s paper, “Approximate Bayesian computationbased on signed roots of log-density ratios.” In Bayesian Statistics 5, (eds: J.O. Berger, J.M.Bernardo, A.P. Dawid and A.F.M. Smith), Oxford University Press.

[148] Liseo, B. (University of Rome, Italy) and Sun, D. (1994). Comments on Professor Nancy Reid’spaper, “Likelihood and Bayesian approximation methods.” In Bayesian Statistics 5, (eds: J.O.Berger, J.M. Bernardo, A.P. Dawid and A.F.M. Smith), Oxford University Press.

[149] Sun, D. (1999). Discussion of “Simulation based optimal design” by Peter Muller. In BayesianStatistics 6, (eds: J.O. Berger, J.M. Bernardo, A.P. Dawid and A.F.M. Smith), Oxford UniversityPress, 470-472.

[150] Sun, D. (1999). Discussion of Another look at conditional Gaussian markov random fields byMichael Lavine. In Bayesian Statistics 6, (eds: J.O. Berger, J.M. Bernardo, A.P. Dawid andA.F.M. Smith), Oxford University Press, 385.

[151] Sun, D. (1999). Discussion of Bayesian models for spatially correlated disease and exposure databy Best, Waller, Thomas, Conlon and Arnold. In Bayesian Statistics 6, (eds: J.O. Berger, J.M.Bernardo, A.P. Dawid and A.F.M. Smith), Oxford University Press, 151-152.

Professional Activities

Organizing Sessions at Professional Meetings

1. Chair of a session at the Intrinsic Bayes Factor Workshop, Purdue University, June 11-12, 1995,Purdue University.

2. Chair of a session at the Sixth Purdue Symposium of Statistics, June, 1998.

3. Organizer of a session of special contributed papers on Development and Applications of Non-informative Priors, 1995 Joint Statistical Meetings, Orlando, Florida, August 13-17.

4. Organizer of an invited session at DALLAS INFORMS meeting, Oct 26-29, 1997, entitled“Bayesian Diagnostics, Assessing Compatibility, Model Selection and Computation.”

5. Organizer of an invited session at 1998 Joint Statistical Meeting, August 9-13, Dallas, entitled“Bayesian Generalized Linear Models.” Section of Bayesian Statistics, American StatisticalAssociation.

6. Organizer of a lunch roundtable session, “Objective Bayesian Analysis.” 1999 JSM, Baltimore.

7. Organizer of an invited session at 1999 Joint Statistical Meeting entitled “Analyzing SpatialEcological and Environmental Data via Hierarchical Models.”

8. Organizer of an invited session “Non/Semi-parametric Regression and Time Series” at Inter-national Society for Bayesian Analysis Sixth World Meeting, Crete, Greece, May 28-June 2,2000.


9. Organizer of two sessions of Topic Contributed Papers: “Bayesian Methods in Economics andMarketing” and “Bayesian Methods in Wildlife and Environmental Studies.” ASA 2001 JointStatistics Meeting, Atlanta, August, 2001.

10. Organizer of two sessions of Topic Contributed Papers: “Spatial-Temporal Modelling” and“Bayesian Application.” ASA 2003 Joint Statistics Meeting, San Francisco, 08/2003.

11. Organizer of two sessions of Topic Contributed Papers: “Bayesian Computing and Modeling”and “Spatial, Temporal Models and Applications.” ASA 2004 Joint Statistics Meeting, Toronto,August, 2004.

12. Organizer of invited talk session “Environmental and Ecological Study,” ICSA 2004 Appliedstatistics meeting, San Diego, June 6-9, 2004.

13. Organizer of invited talk session “Advanced Statistical Methods in Psychological Research,”ASA 2006 Joint Statistics Meeting, Seattle, August 9, 2006.

14. Organizer of invited talk session “Recent Developments of Statistics in Forest, Wildlife, Fisheries,and Ecological Research,” ASA 2007 Joint Statistics Meeting, Salt Lake City, July 31, 2007.

15. Committee of First Student Paper Competition for the SBSS, to attend 2005 JSM.

16. Organizer of invited talk sessions at ASA 2014, 2015, 2016, 2017 Joint Statistics Meetings.

17. Ph.D. Dissertation Examiner for Khangelani Zuma, Department of Statistics, The University ofWaikato, New Zealand. November, 2003.

Other Activities

18. Secretary of ASA, Mid-Missouri Chapter, July 1993–December, 1995.

19. President of ASA, Mid-Missouri Chapter, January 2008–present.

20. Webmaster of homepage and manager of a mailing list of Non-subjective Bayesian StatisticalMethodology with 300 users all over the World, November, 1995–present.

21. Reviewer for the following professional journals.

Annals of Statistics,Biometrika, Biometrics,IEEE Transactions in Reliability,IIE Transactions, Test,Canadian Journal of Statistics,National Science Foundation,

Journal of the American Statistical Association,Communication in Statistics,Journal of Statistical Planning and Inference,Journal of Business and Economics,Statistics and Probability Letters,and Various refereed conference proceedings.

Service

Departmental Service

1. Member of (Ad hoc) Graduate Program Revision Committee, 1993

2. Member of (Ad hoc) Graduate minor committee, 1994

3. Member of Statistics 385 (Regression Analysis) Revision Committee, 1995

4. Member of Statistics 395 (Analysis of Variance) Revision Committee, 1995

5. Member of Statistics 420 (Bayesian Analysis) Revision Committee, 1995

6. Member of endowment Committee (8/93–8/95)

7. Member of Committee on Undergraduate Studies (8/96–7/97)

8. Member of Colloquium Committee (8/96–7/97)

9. Member of Admission and Financial Aid Committee (8/92–7/97, 08/06–now)

10. Member of Computing Committee (8/92–8/98)

11. Chair of Computing Committee (8/94–8/98, 8/01–08/03)

12. Manager of department Unix network system (1/93–8/98)

13. Committee on Graduate Courses and Exams in Statistics (9/99–8/00)


14. Director of Graduate Studies (8/99–7/01, 08/07–now)

15. Chair of Admission and Financial Aid Committee (8/99–7/01, 08/07–now)

16. Advisory committee (08/99–07/05, 08/06–now)

17. Chair of Committee of PhD minor in Statistics (4/01)

18. Chair of space and relocation (11/01–08/03)

19. Member of faculty search committee (08/02—06/03)

20. Chair of faculty search committee (08/04—06/05)

21. Chair of becoming top 25 statistics departments (08/04—06/05)

22. Wrote a proposal (with P.L. Speckman) for a stat computer Lab–an award of $22, 890 from theArts and Science ICF Set Aside funds, 1997.

University Service

23. Member of 30 PhD. dissertation committees and 20 master project committees.

24. Elected Chair of Committee of Fellowship and Awards, Graduate Faculty Senate, The Universityof Missouri-Columbia, 8/2001–7/2003.

25. Graduate Faculty Senate, the University of Missouri-Columbia, 8/2000–7/2003.

26. University of Missouri-Columbia Library Committee, 8/2000–7/2003.

27. Tenure and Promotion Comittee, College of Sciences, Virginia Tech. 8/2005–7/2006

28. Big Data Initiative Committee, University of Missouri, 2014–2016.

29. Search Committee of Dean of College of Arts and Science, University of Missouri, 2017.

Invited Talks at Universities and Conferences

1. “Asymptotic Normality of Linear Functions of Conditional Order Statistics.” the First China-Japan Symposium on Statistics. Beijing, China, November 6-12, 1984.

2. “Necessary Conditions of L1 Convergence of Kernel Regression Estimators.” The Second China-Japan Symposium on Statistics. Fukuoka, Japan, November 4-10, 1986.

3. “Gibbs Sampling for Completing Risks.” University Michigan, Biostat. Dept, 10/1991.

4. “Bayesian Predictive Reliability Demonstration Tests.” University Michigan, Stat., 02/1992.

5. “Bayesian Analysis for poly-Weibull Distributions.” Wayne State University, 03/1992; IUPUI,04/1992; University of Missouri-Columbia, 04/1992.

6. “Bayesian Inferences for a Class of Poly-Weibull Distributions.” The 45th Meeting of the NBER-NSF seminar on Bayesian Inference in Econ. & Stat., Duke, 10/13/1992.

7. “The Reference Prior Under χ2–Distance.” The Fifth Purdue International Symposium onStatistics, Purdue University, 06/1992.

8. “The Stein Identity and its Application.” University of British Columbia, 01/1993.

9. “Integrable Expansions for Posterior Distributions for a Two Parameter Exponential Family.”The First North American New Researchers Meeting, UC Berkeley. 08/1993.

10. “Integrable Posterior Expansions for a Two Parameter Exponential Family.” The First Meetingof the International Society for Bayesian Analysis. San Francisco, August, 1993.

11. “Bayesian Analysis for Poly-Weibull Distributions and Applications in Competing Risks.” The11th Midwest-America Chinese Science & Tech. Conference, St. Louis, 06/18/1994.

12. “ Frequentist Coverage Probability of Confidence Sets From Reference Priors.” Purdue Univer-sity, January 12, 1995.

13. “A Two-Stage Procedure for Selecting the Population with the Largest Mean when the Commonvariance is Unknown.” The Conference on Multiple Decision Theory and Related Topics, inhonor of Shanti S. Gupta, Purdue University, June 8-10, 1995.


14. “Bayesian Design For Dose Responses Penalizing Unexpected Outcomes.”Joint ENAR/ASA/IMS meetings, Richmond, VA, March 17–20, 1996.

15. “Frequentist Properties of Bayesian procedures.” Virginia Tech, 03/21/1996.

16. “Bayesian Design With Penalized Risk.” Purdue University, 04/25/1996.

17. “Integrable Posterior Expansions via Stein’s Identity.” Georgia Tech, 05/16/1996.

18. “Applications of Noninformative priors.” National Institute of Child Health and Human Devel-opment, Bethesda, Maryland, May 23, 1996.

19. “Reference Priors with Partial Information.” Workshop on Default Bayesian Statistical Method-ology, West Lafayette, Indiana, November 1, 1996.

20. “Development of Noninformative priors.” Northern Illinois University, 11/15/1996.

21. “Development of Noninformative priors.” Pennsylvania State University, 02/20/1997.

22. “Bayesian Optimal Designs for Nonlinear Models.” Summer Conference on New Developmentsand Applications of Experimental Design, University of Washington, 06/30/1997.

23. “Hierarchical Models for Estimating Mortality Rates.” 1997 JSM, Anaheim, 08/12/1997.

24. “Bayesian Analysis for Competing Risk Models” Dallas INFORMS meeting, 10/28/1997.

25. “Hierarchical Bayes Estimation of Hunting Success Rates with Spatial Correlations.” U.S. Bu-reau of the Census, 03/27/1998.

26. “Intrinsic Priors for Testing Ordered Exponential Means.” International Conference on Relia-bility and Survival Analysis, Dekalb, 05/24/1998.

27. Invited discussant at the Sixth Valencia International Meeting on Bayesian Analysis, May 30–June 4, 1998, Alcossebre, Spain.

28. “On Bayes and Likelihood.” The Sixth Purdue Symposium of Statistics, 06/18/1998.

29. “Recent Development of Noninformative Priors.” East China Normal University, 07/06/1998.

30. “Hierarchical Linear Mixed Models for Disease Mapping.” East China Normal University,07/07/1998.

31. “Default Bayesian Analysis for Generalized Linear Models.” 1998 JSM, Dallas, 08/10.

32. “Hierarchical Models in Wildlife Abundance Estimation.” Duke University, 09/18/1998.

33. “Random Effects in Generalized Linear Mixed Models.” Duke University, 09/22/1998.

34. “Bayesian Hierarchical Models for Small Area Estimation with Applications in Sampling Survey.”Research Triangle Institute, 10/15/1998.

35. “Hierarchical Linear Mixed Models for Multinomial Logit Distributions.” National Institute ofStatistics Sciences, 11/17/1998.

36. “Bayesian Hierarchical Models for Small Area Estimation with Applications in Sampling Survey.”University of Georgia, 12/3/1998.

37. “Space-Time Interaction with Disease Mapping.” University of North Carolina-Chapel Hill,Biostatistics, 01/20/1999.

38. “Hierarchical Models for Spatially Correlated Data with Applications in Sampling Survey.” Uni-versity of Minnesota, 02/15/1999.

39. “Generalized Linear Mixed Models and Spatio-Temporal Interaction.” ASA North CarolinaChapter, 03/20/1999.

40. “Hierarchical Models for Spatially Correlated Data.” University of North Carolina-Charolette,04/15/1999.

41. “Recent Developments In Hierarchical Linear Mixed Models.” University of Connecticut, 04/23/1999.

42. “Existence of the MLE and Propriety of Posteriors for a General Multinomial Choice Model.”University of North Carolina-Chapel Hill, Statistics, April 28, 1999.

43. “Random Effects in Generalized Linear Mixed Models.” International Workshop on ObjectiveBayesian Methodology, Valencia, Spain, June 11–13, 1999.


44. “Bayesian Smoothing for Nonparametric Regression.” 1999 Joint Statistical Meeting, Baltimore,August 9–13.

45. “Existence of the MLE and propriety of posteriors for multinomial choice models.” InternationalSociety for Bayesian Analysis Sixth World Meeting, Crete, Greece, 05/30/2000.

46. “Some Recent Development in Joint Disease Mapping.” The AMS Summer Research Conferenceon Bayes, Frequentist and Likelihood Inference: a Synthesis, Mt. Hollyoke, MA, 07/10/2000.

47. “Objective Priors under the Sequential Experimentation.” The Third International Meeting inObjective Bayesian Analysis. Ixtapa, Mexico, September 23, 2000.

48. “Joint Disease Mapping and Improving the Estimates of Mortality Rates.” Duke University, Feb6, 2001.

49. “Bayesian Analysis for Multinomial Distributions Under Informative and Noninformative Pri-ors.” Duke University, Feb 16, 2001.

50. “Bivariate BAYES Method for Improving the Estimates of Mortality Rates with 2–Fold CARModel.” 2001 Joint Statistical Meeting, Atlanta. August 8, 2001.

51. “Small Area Estimation Using Bayesian Method.” Keynote Speaker, the Eighth Wildlife SocietyAnnual Meeting, Reno, September 29, 2001.

52. “Hierarchical Models for Small Area Estimation with Applications in Sampling Survey.” Thekeynote speaker of the ASA South Florida Chapter – Mini Conference, 01/31/2003.

53. “Bayesian Analysis for Vector-Autoregressive Models.” Duke University, March 7, 2003.

54. “Hierarchical Models for Small Area Estimation with Applications in Sampling Survey.” Uni-versity of Cincinnati, May 2, 2003.

55. “Partial Informative Normal and Spline Smoothing.” Fourth International Workshop on Objec-tive Bayesian Methodology, Aussois, France, June15-20, 2003.

56. “Estimation of the Precision and Covariance Matrices in Star-Shaped Models.” The 7th PurdueInternational Symposium on Statistics. June 19–24, 2003.

57. “Estimation of the Multivariate Normal Precision and Covariance Matrices in a Star-shapeModel.” University of South Carolina, September 23, 2003.

58. “Characterizing and Eradicating Autocorrelation in MCMC Algorithms.” University of Florida,October 23, 2003.

59. “Characterizing and Eradicating Autocorrelation in MCMC Algorithms.” York University, De-cember 3, 2003.

60. “Characterizing and Eradicating Autocorrelation in MCMC Algorithms.” University of Valencia,December 8, 2003.

61. “Model Section for Vector Autoregressive (VAR) Models.” International Society for BayesianAnalysis (ISBA) 2004 World Meeting, Vina del Mar, Chile, May 26, 2004,

62. “Bayesian Hierarchical Linear Mixed Models for Additive Smoothing Splines,” 2004 Joint Statis-tics Meeting, Toronto, August 9, 2004.

63. “Objective Bayesian Semiparametric Models and Space-Time Interaction.” Iowa State Univer-sity, September 13, 2004.

64. “Objective Bayesian Semiparametric Models and Space-Time Interaction.” Virginia Tech, Jan-uary 28, 2005.

65. “Objective Bayesian Analysis for Spatial-Temporal Models.” Tutorial of 1.5 hours at The FifthInternational Workshop on Objective Bayesian Methods, Branson, USA, June 4–9, 2005.

66. “Objective Priors for a Multivariate Normal Model.” The Eighth Valencia International Meet-ings on Bayesian Statistics and ISBA Eighth World Meeting on Bayesian Statistics. Benidorm(Alicante, Spain), June 1–6, 2006.


67. “Bayesian Spline Smoothing of Density Estimation via Hazard Rates.” The Fifth Workshopon Bayesian Nonparametrics, Methodology, Theory and Applications, Jeju Grand Hotel, Karea,June 16–18. 2006.

68. “Objective Bayesian Analysis for Multivariate Spline Smoothing.” 2006 Joint Statistics Meeting,Seattle, August 9, 2006.

69. “Objective Bayesian Analysis for Graphical Models.” Bayesian Focus Week on Random Matrices,SAMSI, NC, November 1, 2006.

70. “Objective Bayesian Analysis for a Multivariate Normal Model.” Imperial College, London, UK,December 7, 2006.

71. “Bayesian Analysis for Normal Distributions.” University of Southampton, UK, Dec. 8, 2006.

72. “Objective Bayesian Analysis for Multivariate State Space Models.” The 15th InternationalConference on Interdisciplinary Mathematical & Statistical Techniques. Shanghai, P.R.China,May 21, 2007.

73. “Hierarchical Models for Adjusting Nonresponses Bias.” A special presentation (one hour) atUS Fishery and Wildlife Service, Washington D.C., May 30, 2007.

74. “Choices of Objective Priors and Bayesian Analysis for Spatial-Temporal Models.” Tutorial oftwo sessions of 1 hour each at the Sixth International Workshop on Objective Bayesian Methods,Rome, Italy, June 8-12, 2007.

75. “Objective Bayesian Model Selection for a Linear Mixed Model.” 2007 Joint Statistics Meeting,Salt Lake City, July 31, 2007.

76. “Objective Bayesian Analysis for a Multivariate Normal Model.” University of Missouri-KansasCity, November 22, 2007.

77. “Objective Bayesian Model Selection for a Linear Mixed Model.” International Conference onStatistical Paradigms: Recent Advances and Reconciliations, Kolkata, India, Jan. 1-4, 2008.

78. “Objective Bayesian Analysis for Multivariate Normal Models.” Washington University-St.Louis, April 15, 2008.

79. “Choices of Objective Priors.” The 16th International Conference on Interdisciplinary Mathe-matical & Statistical Techniques, Memphis, TN, USA, May 15-18, 2008.

80. “Formal Rule of Reference Priors.” International Indian Statistical Association (IISA) Confer-ence “Frontiers of Probability & Statistical Science,” Storrs, Connecticut, May 22-25, 2008.

81. “A Linear Mixed Model, Fixed or Random Effects?”. The 2008 Classification Society of NorthAmerica (CSNA) meeting, St. Louis, USA, June 5, 2008.

82. “Objective Bayesian Analysis.” The first IMS-China International Conference, Hangzhou, China,June 11-13, 2008.

83. “One-Way ANOVA, Fixed or Random Effects?” The Ohio State University, Columbus, OH,USA, October 9, 2008.

84. “A Linear Mixed Model, Fixed or Random Effects?”. University of Valiencia, December 10,2008.

85. “Formal Rule of Reference Priors.” International Workshop on Objective Bayesian Methods,University of Pennsylvania, Philadelphia, June 5-9, 2009.

86. “Bayesian Hierarchical Models for Recognition-Memory and Other Psychological Experiments”.2009 Summer Program on Psychometrics, SAMSI, North Carolina, July, 14, 2009.

87. “A Linear Mixed Model, Fixed or Random Effects?”. ISI 2009, Durban, South Africa, August17, 2009.

88. “Bayesian Hierarchical Models for Cancer Incidence Based on Misaligned Models”. The 6thInternational, Interdisciplinary Conference on Geomedical Systems, (GEOMED/SAMSI 2009),Charleston, SC, USA, November 15, 2009.


89. “The Formal Definition of Reference Priors.” North Carolina State University, February 25,2010.

90. “Objective Reference Priors”, University of Virginia. April 23, 2010.

91. “The Formal Definition of Reference Priors”, University of North Carolina–Chapel Hill, April27, 2010,

92. “Bayesian Hierarchical Models for Recognition-Memory and Other Psychological Experiments”,The 2010 IMS Asian Meeting and The 4th International Forum on Statistics of Renmin Univer-sity of China, Beijing, China July 12, 2010.

93. “Bayesian Spatial and Temporal Models for Cancer Incidence and Survival”, 2010 ShanghaiInternational Biostatistics Workshop, Shanghai, China, July 20, 2010.

94. “Summary and Future Work of Fundamentals of Spatial Modeling”, SAMSI, October 13, 2010.

95. “Hierarchical Models for Small Area Estimation with Applications in Sampling Survey”, TheUniversity of Science and Technology, China, June 1, 2011.

96. “Objective Bayesian Analysis for a Multivariate Normal Model” The University of Science andTechnology, China, June 2, 2011.

97. “Applications–Spatio-Temporal Models”, The 2011 International Workshop on Objective BayesianMethods, Shanghai, June 11, 2011.

98. “Bayesian Analysis for the ECMO Clinical Trial”, The 2011 Shanghai Bio-statistics Forum, withpanel discussion, Shanghai, June 14, 2011.

99. “Bayesian Analysis of Variance”, Purdue University, October 7,2011.

100. “Bayesian Analysis of Variance”, Michigan State University, November 3, 2011.

101. “ Statistcs Education and Interdiscipline Research”, Qinghai University for Nationalities, June8, 2012.

102. “ Statistcs Education and Interdiscipline Research”, Qinghai Normal Univerity, June 9, 2012.

103. “ Bayesian Model Selection for a Linear Model with Grouped Covariates” The 8th InternationalPurdue Symposium on Statistics, June 22, 2012.

104. “ Bayesian Model Selection for a Linear Model with Grouped Covariates” The ISBA 2012 WorldMeeting, Kyoto, Japan; June 28, 2012.

105. “Bayesian ANOVA Models”, The 2nd IMS – Asia Pacific Rim Meeting, Tsukuba, Japan; July3, 2012.

106. “ Bayesian Model Selection for a Linear Model with Grouped Covariates” Oklahoma StateUniversity, October 12, 2012.

107. “Multivariate CAR Models for Misaligned Regions”, International Spatial Statistics Conference,University of Miami, December 13–15, 2012.

108. “Discussion of “Advances in approximate Bayesian computation based on modified loglikelihoodratios” by L. Ventura, E. Ruli and W. Racugno, at Recent Advances in Statistical Inference:Theory & Case Studies, Padova, Italy – March 21, 2013.

109. “Objective Bayesian Analysis for Some Biomedical Models”, Jiangsu University, June 20, 2013.

110. “FDR and Bayesian Multiple Comparisons”, Boehringer Ingelheim, Shanghai, July 24, 2013.

111. “Applications of Objective priors”, East China Normal University, July 13, 2013.

112. “Bayesian Smoothing of Multivariate Models”, Duke University, Oct 18, 2013.

113. “The Formal Reference Priors for a General Class of Divergence”, Rutgers University, November13, 2013.

114. “Bayesian Smoothing of Multivariate Models”, The Iowa State University, December 2, 2013.

115. “The Formal Objective Bayesian Methods”, The 2013 International Workshop on ObjectiveBayesian Methods, Duke University, December 15, 2013.


116. “The Formal Reference Priors for a General Class of Divergence”, The Ninth ICSA InternationalConference: Challenges of Statistical Methods for Interdisciplinary Research and Big Data, 20-23December, 2013 Hong Kong Baptist University.

117. “The Formal Reference Priors for a General Class of Divergence”, Frontiers of HierarchicalModeling in Observational Studies, Complex Surveys and Big Data: A Conference HonoringProfessor Malay Ghosh, University of Maryland, May 30, 2014.

118. “Applications of Objective (Noninformative) priors”, East China Normal University, Shanghai,China, July 19, 2014.

119. “Bayesian Smoothing and Risk Analysis of Multivariate Models”, 2014 Joint Statistical Meeting.

120. “Becent Development of Reference Priors under a General Class of Divergence”. The First lnter-national Workshop on Bayesian, Fiducial, and Frequentist Inference and Statistical Foundations,November10-14, 2014, Shanghai, China.

121. “Bayesian Analysis of Multivariate Smoothing Splines”, The Workshop on Big Data Opportu-nities, Challenges and Innovations, Tsinghua Sanya International Mathematics Forum in Sanya,China, Dec 27-30, 2014.

122. “Bayesian Analysis of Multivariate Smoothing Splines”, at University of Chile, January 9, 2015.

123. “Bayesian Analysis of Multivariate Smoothing Splines”, The National University of Singapore,February 4, 2015.

124. “Bayesian Analysis of Multivariate Smoothing Splines”, at Nanyang Technological University,Singapore, February 5, 2015.

125. “Bayesian Methods of Multivariate Functional Analysis”, Su Zhou University, March 20, 2015.

126. “Objective Bayesian Analysis under a General Class of Divergence”, International FocuStatWorkshop on CD Distributions, Oslo, May 11, 2015.

127. “Bayesian Analysis of Multivariate Smoothing Splines”, US Census Bureau, June 15, 2015.

128. “Recent Development of Reference Priors under a General Class of Divergence”. 2015 JointStatistical Meeting, Seattle, August 11, 2015.

129. “Objective Bayesian Anslysis under Semi-invariance Structure” University of South Carolina,March 21, 2016.

130. Discussion of The Use of Rejection Odds and Rejection Ratios in Testing Hypotheses. The 3rdWorkshop on Fusion Learning, BFF inference and Statistical Foundations, Rutgers Univesrity,April 11, 2016.

131. “Smoothing Spline Analysis of Bond Trading Data”, 3rd Conference of the International Societyfor Non-Parametric Statistics, Avignon, France, June 13, 2016.

132. “Objective Bayesian Anslysis under Partial Invariance“, 2016 Joint Statistical Meeting, Chicago,August 2, 2016.

133. “Spatial Bayesian Hierarchical Model for Small Area Estimation of Proportions with Con-straints” Small Area Estimation 2016, Maastricht, Netherlands, Augest 19, 2016.

134. “Partially Informative Normal and Bayesian Partial Spline”, University of NebraskaLincoln,September 30, 2016.

135. “An Objective Prior for Hyperparameters in Normal Hierarchical Models”, Recent Developmenton Latent Variables, Columbia, South Carolina, October 13, 2016.

136. “Bayesian Partial Spline and Yield Curve of Chinese Bonds” Worcester Polytechnic Institute,November 14, 2016.

137. “An Objective Prior for Hyperparameters in Normal Hierarchical Models”, Brigham YoungUniversity, March 09, 2017.

138. “Bayesian Partial Spline and Yield Curve of Chinese Bonds”, Purdue University, April 7, 2017.

139. “Estimation and Prediction in the Presence of Spatial Confounding”. The Iowa State University,April 25, 2017.


140. Objective Prior for Hyperparameters in Normal Hierarchical Models”, US Census Bureau, July17, 2018.

141. “An Objective Prior for Hyperparameters in Normal Hierarchical Models”, 2017 Joint StatisticalMeeting, Baltimore, August 1, 2017.

142. Note on Bayesian Data Fusion with Misalignment, SAMSI, Oct 1, 2018.

143. Bayesian Analysis of Covariance Matrix of Multivariate Normal Distribution with a New Classof Priors, University of Maryland, October 4, 2018.

144. Bayesian Analysis of Covariance Matrix of Multivariate Normal Distribution with a New Classof Priors, US Bureau of Labor Statistics. October 5, 2018.

145. Data Fusion with Misalignment from Aggregation for Disclosure Avoidance, US Census Bureau,November 16, 2018.

146. Bayesian Analysis of Covariance Matrix of Multivariate Normal Distribution with a New Classof Priors, CFE-CMStatistics 2018, December 15, 2018.

Other Presentations

1. “Bayesian Sequential Reliability Demonstration Tests.” The Fourth Valencia InternationalBayesian Meeting, Spain, April, 1991.

2. “Integrable Posterior Expansions for a Two Parameter Exponential Family.” University ofMissouri-Columbia, February, 1993.

3. “Reference Prior Bayesian Analysis for Normal Mean Products.” University of Missouri-Columbia,March, 1994.

4. “Inference on a Product of Normal Means with Unknown Variances.” Joint Statistical Meeting,Orlando, August, 1995.

5. “Frequentist Validity of Posterior Quantiles For a Two Parameter Exponential Family.” JointStatistical Meeting, Orlando, August, 1995.

6. “Reference Priors With Partial Information.” Kullback Memorial Research Conference, GeorgeWashington University, May 24-25, 1996.

Documents

Dongchu Sun’s Curriculum Vitae CV.pdf · Dongchu Sun’s Curriculum Vitae 25 { 5 8. Luyan Dai (2005). Bayesian Smoothing of Density Estimation via Hazard Rates. 9. Xiaoyan Lin (2005)