Xiaoyan(Iris) Lin. University of South Carolina Office: B LeConte College Fax: Columbia, SC, 29208

Transcription

1 Xiaoyan(Iris) Lin Department of Statistics University of South Carolina Office: B LeConte College Fax: Columbia, SC, Education Doctor of Philosophy in Statistics August 2008 University of Missouri - Columbia, Missouri, U.S.A. Dissertation title: Bayesian Hierarchical Models for the Memory-Recognition Experiment Advisor: Dr. Dongchu Sun GPA 4.0/4.0 Master of Science in Statistics December 2005 University of Missouri - Columbia, Missouri, U.S.A. Specialized in Mathematical Statistics Dissertation title: Exploring the General Definition of Two-dimensional Reference Priors Bachelor of Science in Statistics July 2001 East China Normal University, Shanghai, China Specialized in Probability and Statistics Certified, Program for Excellence in Teaching Spring 2005 University of Missouri- Columbia, Missouri, U.S.A. Experience Assistant Professor August 2010-present Department of Statistics, University of South Carolina, Columbia, SC, USA Visiting Assistant Professor August 2008-August 2010 Department of Statistics, University of South Carolina, Columbia, SC, USA Taught statistical courses (Statistical Methods I, Statistical Methods II, and Nonparametric Statistical Methods); conducted individual and collaborative research (e.g., participated in the application of a NIH grant about the agreement webs project, PI: Don Edwards). Page 1 of 5

2 Graduate Fellow January 2008-May 2008 Statistical and Applied Mathematical Sciences Institute (SAMSI), RTP, NC USA Participated in the program on Risk Analysis, Extreme Events and Decision Theory; Developed the reference prior for multivariate extreme distributions. Graduate Research Assistant August 2007-August 2008 University of Missouri-Columbia, Department of Statistics, Columbia, MO 65201, USA Developed Hierarchical Bayesian Models to for the memory processes and the memoryrecognition experiments; apply objective priors (constant prior, right Harr prior, etc.) to improve the estimation of memory parameters. Graduate Instructor August 2005-May 2007 University of Missouri-Columbia, Department of Statistics, Columbia, MO USA Taught independently for the course Introduction to Probability and Statistics II. Graduate Teaching Assistant August 2003-May 2005 University of Missouri-Columbia, Department of Statistics, Columbia, MO, USA Taught statistical software Minitab for the course Elementary Statistics ; supervised the computer lab. Research Interests Bayesian Hierarchical Modeling Objective Bayesian Analysis Bayesian Survival Analysis Item Response Theory Agreement Measures Publications X. Lin and L. Wang (2011). "Bayesian proportional odds models for analyzing current status data: univariate, clustered, and multivariate. Accepted by Communications in Statistics Simulation and Computation. L. Wang and X. Lin (2011). Two Bayesian Approaches for Analyzing Case 2 Intervalcensored Data under the Semiparametric Proportional Odds Model. Minor revision Page 2 of 5

3 submitted to Statistics and Probability Letters. B. Cai, X. Lin, and L. Wang (2011). Bayesian Proportional Hazards Model for Current Status Data Using Monotone Splines. Revision submitted to Computational Statistics and Data Analysis. X. Lin and D. Sun (2010). A Note on the Existence of the Posteriors for One-way Random Effect Probit Models. Statistics and Probability Letters (2010), vol. 80, X. Lin and L. Wang (2010). A Semiparameteric Probit Model for Case 2 Intervalcensored Failure Time Data. Statistics in Medicine (2010), vol. 29, X. Lin, D. Sun, P. Speckman, and J. Rouder (2009). Constant Prior for the Recognition- Memory Model. Manuscript. X. Lin and D. Sun (2009). Objective Bayesian Analysis for Two-way Random Effect Probit Models. Manuscript. X. Lin, D. Sun, and J. Berger (2008). The Formal Definition of Reference Priors for Multi-dimensional Cases. Technical Report. X. Lin and D. Sun (2007). Objective Bayesian Analysis in Memory Study, 2007 Joint Statistical Meeting Proceedings. Works in Progress L. Wang and X. Lin (2011). A Bayesian Semiparametric Accelerated Failure Time Model for Arbitrarily Censored Data with Measurement Errors. X. Lin (2011). Nonparametric Link for Dichotomous Response Data. X. Lin (2011). Bayesian Generalized Odds Ratio Hazards Models for Current Status Data. X. Lin, J. Berger, and D. Sun (2009). Reference Priors under Partial Invariance. H. Chen, D. Edwards, and X. Lin (2009). A Bayesian Hierarchical Model for Robust Disease Diagnoses. X. Lin, H. Chen, and D. Edwards (2009). Objective Bayesian Analysis for the Agreement Web about Disease Diagnoses. Professional Activities/Presentations Page 3 of 5

4 Presented a talk A Semiparametric Probit Model for Interval-Censored Failure Time Data, Department of Statistics, University of South Carolina, February, Presented an invited talk A Semiparameteric Probit Model for Case 2 Interval-censored Failure Time Data, Department of Epidemiology and biostatistics, University of South Carolina, November, Presented an invited talk Reference Priors under Partial Invariance at O-Bayes09, Philadelphia, June, Presented a formal talk Objective Bayesian Analysis in the Memory Recognition Experiment, Department of Statistics, University of South Carolina, October, Presented a topic contributed talk Objective Bayesian Analysis in Memory Study at JSM, Salt Lake City, Utah, July, Presented a poster Exploring the General Definition of Two-dimensional Reference priors in SAMSI summer 2007 program on Challenges in Dynamic Treatment Regimes and Multistage Decision-Making, June 18-29, Presented a contributed talk "Bayesian Hierarchical Models for the Two-Component Memory Process" at ENAR Spring Meeting, Atlanta, Georgia, March, Journal Reviewer Journal of Statistical Planning and Inference Computational Statistics and Data Analysis Professional Societies American Statistical Association Institute of Mathematical Statistics Honors Superior Graduate Student Achievement Award, , Graduate school, University of Missouri-Columbia. Travel award to Joint Statistical Meeting 2007, Graduate school, University of Missouri Columbia. Three first-class scholarships, , Department of Statistics, East China Normal Page 4 of 5

5 University. Computer Skills Operation platform: Windows, UNIX Statistical/mathematical software: SAS, SPSS, MINTAB, R/S-PLUS, Mathematica. Programming language: R, FORTRAN. Text formatting: LaTex, Word, PowerPoint. Page 5 of 5