Chen Zehua

 

 

Chen Zehua

Chen Zehua


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) 65166307 (office)

(65) 84995559 (Mobile)

(65) 68723919 (fax)

Education

B.S., Wuhan Univ. (1981)

M.S., Univ. of Iowa (1985)

Ph.D., Univ. of Wisconsin-Madison (1989)

Current Research Interests

Model selection criteria.

Feature selection with high dimensional space.

Statistical genetics.


Publications


Publication List

Recent Preprints

o Sequential Lasso cum EBIC for feature selection with ultra-high dimensional feature space (Journal Link) (pdf)

o Extended BIC for linear regression models with diverging number of relevant features and high or ultra-high feature spaces. (Journal Link)

o A two-stage penalized logistic regression approach to case-control genome-wide association studies. Supplementary document (Journal Link)

o Selection Consistency of EBIC for GLIM with Non-canonical Links and Diverging Number of Parameters. Supplementary document (arXiv link)

Monograph

Ranked Set Sampling: Theory and Applications

Z. Chen, Z. D. Bai and B. K. Sinha

Springer ©2004

Table of Contents

Statistical Methods for QTL Mapping

Z. Chen

Chapman & Hall/CRC © 2014

Selected Pages


Teaching Corner


FMS1203S: Randomness in scientific thinking

Course Outline

The purpose of this seminar is to introduce students to the roles of random-
ness in scienti c thinking. Some of the topics covered include the following:

Instruction Notes

Week 1 Introduction.

Week 2 Problem with sampling. Group 1 Group 4

Week 3 Experimental design. Group 1 Group 2 Group 3 Group 4 Group 5

Week 4 Hypothesis testing. Group 1 Group 2 Group 3 Group 4 Group 5

Week 5 Misleading with or without data Group 1 Group 2 Group 3 Group 4 Group 5

Week 6 Statistics and Environment. Group 1 Group 2 Group 3 Group 4 Group 5

Week 8 Misleading reports in the Media. Group 1 Group 2 Group 3 Group 4 Group 5

Week 9 Reading assignment. Group 1 Group 2 Group 3 Group 4 Group 5

Week 10 Reading assignment. Group 1 Group 2 Group 3 Group 4 Group 5

Week 11 Reading assignment. Group 1 Group 2 Group 3 Group 4 Group 5

Week 12 Reading assignment. Group 1 Group 2 Group 3 Group 4 Group 5

Week 13 Instruction of Final report. Group 1 Group 2 Group 3 Group 4 Group 5

FMS1204S: Fraud, deception and data

Course Outline

The purpose of this seminar is to explore the relationship
between fraud and deception and statistics. Very often
misleading claims arise from an ignorance of basic statistical
ideas, but statistical methods can also be abused knowingly in
fraudulent behavior. On the other hand, statistical methods are
also commonly used to detect and uncover fraud and
dishonesty. This seminar will discuss the role of statistics in
uncovering deception in areas such as:

Instruction Notes

Week 1 Introduction.

Week 2 Types of medical data and misinterpretation.

Week 4 Surveys and opinion polls.

Week 5 Data and consumer: danger and opportunity. Group 1 Group 5 Group 2 Group 4

Week 6 Uncertainty and controversy in environmental research. Group 1 Group 2 Group 3 Group 4 Group 5

Week 8 Fraud in the financial world. Group 1 Group 2 Group 3 Group 4 Group 5

Week 9 Fraud in archaeology. Group 1 Group 2 Group 3 Group 5

Week 10 Reading assignment Group 1 Group 2 Group 3 Group 4 Group 5

Week 11 Instruction. Group 2 Group 3 Group 5

Week 12 Instruction. Group 1 Group 2 Group 3 Group 5

Week 13 Instruction. Group 1 Group 3 Group 5


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Chen Zehua <stachenz@nus.edu.sg> 5 APR 2012