Applied mathematics and statistics are very important and scientific tools used in social sciences, natural sciences, engineering, medical and biological sciences, economics and finance, and many other fields in colleges from our university. The purpose of this international conference is to establish cooperation and collaboration between researchers in applied mathematics and statistics from Northwest A and F University and worldwide well-known professors, experts, and researchers. Several professors and experts from domestics and aboard will be invited to deliver colloquium talks, conduct research projects with researchers from our applied and statistics group as well as other related areas.

　　应用数学与应用统计学是自然科学、社会科学、工程科学、医学科学以及生物科学中非常重要的科学工具。本次国际研讨会的目的是建立西北农林科技大学相关研究人员和学者与国内外著名专家、学者、教授在应用数学学科和应用统计学科之间的交流与合作。我们邀请该领域的国内外著名专家、教授做一系列专题报告，对西北农林科技大学应用数学和统计学课题组以及相关学科给予指导并进行合作研究。

Series talk III.

　　Invited Speaker: Dr. Hanfeng Chen(Bowling Green State University)

　　Title: Confidence intervals for the mean of a population containing many zero values under unequal probability Sampling

　　Abstract: In many applications, a finite population contains a large proportion of zero values that make the population distribution severely skewed. An unequal-probability sampling plan compounds the problem further, and as a result the normal approximation to the sample mean distribution via the central limit theorem has poor precision. Complex designs also make it hard to pin down useful likelihood functions, hence a direct likelihood approach is not an option. In this paper, we propose a pseudo-likelihood approach. The proposed pseudo-log-likelihood function is an unbiased estimator of the log-likelihood function when the entire population is sampled. When the inclusion probabilities are related to the unit values, the pseudo-likelihood intervals are superior to existing methods in terms of the coverage probability, the balance of non-coverage rates on the lower and upper sides, and the interval length. An application with a data set from the Canadian Labor Force Survey-2000 also shows that the pseudo-likelihood method performs more appropriately than other methods.

　　报告时间：2011年5月26日 星期四 上午10:00-11:00
　　
　　报告地点：理学院二楼多媒体教室
　　
　　报告人简介 
　　
　　Dr.  HANFENG CHEN

　　Graduate Coordinator and Professor

　　Department of Mathematics and Statistics

　　Bowling Green State University

　　Bowling Green, Ohio 43403, USA

　　E-mail: hchen@bgsu.edu

　　I. Academic Degrees

　　•  Ph.D. University of Wisconsin-Madison, 1990.  Major in Statistics; minor in Computer Science and Mathematics.

　　• M.A. Wuhan University (China), 1985. Major in Statistics.

　　• B.S. Wuhan University (China), 1982. Major in Mathematics.

　　II. Academic Positions

　　• Professor, Bowling Green State University, 2002 to present.

　　• Visiting Professor, Wuhan University (China), 2005 to present.

　　• Visiting Professor, York University (Canada), 2007.

　　• Associate Professor, Bowling Green State University, 1996 to 2002.

　　• Visiting Associate Professor, University of Waterloo, 1998.

　　• Assistant Professor, Bowling Green State University, 1990 to 1996.

　　• Teaching Assistant, University of Wisconsin-Madison, 1987 to 1990.

　　• Teaching Assistant, University of Rochester, 1986 to 1987.

　　• Lecturer, Wuhan University (China), 1985 to 1986.

　　III. Research Interests

　　Finite mixture models, statistical genetics, analysis of transformed data, statistical process control, empirical likelihood methods, multivariate analysis, robust statistical inference.

　　IV. Ten Selected Publications

　　1. Chen, H., Chen, J. and Chen, S.Y. (in press). Confidence intervals for the mean of a population containing many zero values under unequal probability sampling. The Canadian Journal of Statistics.

　　2. Wu, X., Chen, H., and Liu, Y. (2008). Interval mapping for quantitative trait loci detection in finite mixture models with general kernel functions. Communications in Statistics-Theory and Methods, Statistics in Genetics 37: 803-814.

　　3. Deng, W., Chen, H., and Li, Z. (2006). A logistic regression mixture model for interval mapping of genetic trait loci affecting binary phenotypes. Genetics 172: 1349-1358.

　　4. Chen, H. and Chen, Z. (2005). Asymptotic properties of the remedian. Journal of Nonparametric Statistics 17: 155-165.

　　5. Chen, H., Chen, J. and Kalbeisch, J.D. (2004). Testing for a finite mixture model with two components. Journal of Royal Statistical Society, Ser. B  66: 95-115.

　　6. Chen, H., Chen, J. and Kalbeisch, J.D. (2001). A modified likelihood ratio test for homogeneity in finite mixture models. Journal of Royal Statistical Society, Ser. B 63: 19-29.

　　7. Chen, H. (1995). Tests following transformations. The Annals of Statistics 23: 1587-1593.

　　8. Chen, H. (1994). A multivariate process capability index over a rectangular solid tolerance zone. Statistica Sinica 4: 749-758.

　　9. Chen, H. and Loh, W.Y. (1992). Bounds on AREs of tests following Box-Cox transformations. The Annals of Statistics 20: 1485-1500.

　　10. Chen, H. (1990). On the accuracy of approximate intervals for a binomial parameter. Journal of the American Statistical Association 85: 514-518.

　　V. Membership in Professional Organizations

　　• American Statistical Association (since 1988).

　　• Institute of Mathematical Statistics (since 1988).

　　• International Chinese Statistical Association (since 1987).

　　　　　　　　　　　　理学院
　　　　　　　　　　　　2011年5月24日