Chen Zehua

Associate Professor of Statistics
Department of Statistics and Applied Probability
National University of Singapore
3 Science Drive 2, Singapore 117543
Republic of Singapore

stachenz@nus.edu.sg

(65) 6516-6307 (office)
(65) 6569-5659 (home)
(65) 6872-3919 (fax)

Curriculum Vitae 

Education

  • B.S., Wuhan Univ. (1981)
  • M.S., Univ. of Iowa (1985)
  • Ph.D., Univ. of Wisconsin-Madison (1989)

Current interests

  • Nonparametric regression and related topics.
  • Bootstrap methods.
  • Ranked set sampling.
  • Degradataion data analysis.
  • Statistical genetics.

Full CV

 

Publications

         Complete list  (Updated August 4, 2006)

Recent Preprints

    • Linkage Disequilibrium mapping of quantitative-trait loci by selective genotyping. (Full text)
    • Extreme rank selections for linkage analysis of quantitative trait loci using selected sib pairs ( Full text pdf )
    • Mixture Generalized Linear Models for Multiple Interval Mapping of Quantitative Trait Loci in Experimental Crosses  (Abstract)  
    • A new approach to interval mapping of quantitative trait loci using sib pairs. (Abstract)  

Monograph

Ranked Set Sampling: Theory and Applications

Z. Chen,   Z. D. Bai and B. K. Sinha

Springer ©2004

                        Preface (PDF file)

                  Table of contents (PDF file)

 

Software

The package migtlm:   Multiple interval genetic trait loci mapping

       Source code: migtlm.R

       Instruction:    How to use?

       Reference:    Mixture Generalized Linear Models for Multiple Interval Mapping of Quantitative Trait Loci in Experimental Crosses

 

Teaching Corner

ST5206: Generalized Linear Models (2007/2008 Semester I)

                           Course Information

                           

                            Note: The following lecture notes are subject to modifications.


                            Lecture Notes 1:  General Theory of GLIM   (updated 22/08/2007)

                                             Introduction to R

                                             Tutorial 1

                                             Tutorial 2

                            Lecture Notes 2:  GLIM for binary data   (last updated 21/09/2007)

                                            (  R codes for the example )           

                                                        Tutorial 3

                            Lecture Notes 3:  GLIM for data with mean proportional to variance  (updated 3/10/2007)

                                             (  R codes for the example )           

                                                        Tutorial 4  ( Data set for Tutorial 4) R code

 

                                            Project Assignment  ( Data set for the project )

 

                            Lecture Notes 4:  GLIM for data with constant coefficient of variation (updated 23/10/2007)

                                             Rcodes for examples:  

                                                   Car insurance

                                                   Drosophila melanogaster (Data set)

                                                        Tutorial 5  ( Data set )  R codes for solution

                            Lecture Notes 5:  Multivariate GLIM  for polytomous response data (updated 30/10/2007)

                                             Tutorial 6                

                            Lecture Notes 6:  Quasi-likelihood and estimating equations

                           Lecture Notes 7:  Models with nonlinear parameters and model diagnostics         

                                                         Tutorial 7   (Data1,  Data2)  R codes

 

 

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