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Mosuk Chow

Mosuk Chow

Main Content

  • Senior Scientist, Director of MAS Program
315 Thomas
University Park, PA 16802
Phone: (814) 863-8128


  1. B.S. in Mathematics, Chinese University of Hong Kong
  2. M.S., Ph.D. in Statistics, Cornell University

Selected Publications

M. Chow and S. Thompson. 2003. S estimation with link-tracing sampling designs: a Bayesian approach. Survey Methodology 29(2): 197-205.

Z. D. Bai, C. R. Rao, M. Chow and D. Kundu. 2003. An efficient algorithm for estimating the parameters of superimposed exponential signals. Journal of Statistical Planning and Inference 49: 23-34.

M. Chow and D. Fong. 1992. Simultaneous estimation of the Hardy-Weinberg proportions. The Canadian Journal of Statistics 20: 291-296.

Q. Yu and M. Chow. 1991. Minimaxity of the empirical distribution function. Annals of Statistics 19: 935-951.

Z. D. Bai and M. Chow. 1991. Inadmissibility of the MLE in the sequential estimation of the size of a population. Biometrika 78: 817-823.

M. Chow. 1990. Admissibility of the MLE for simultaneous estimation of the negative binomial problems. Journal of Multivariate Analysis 33: 212-219.

M. Chow. 1987. A complete class theorem for noncentrality parameter. Annals of Statistics 15: 800-804.

Research Interests

Biostatistics, Statistical decision theory, sampling methods.

Dr. Chow's areas of research interest include biostatistics, statistical decision theory and sampling methods.

An important question in statistical decision theory is to characterize the set of all optimal prodecures. An admissible procedure is optimal in the weak sense that it cannot be outperformed by another procedure completely in all circumstances. It is thus desirable to find necessary conditions for admissible procedures. Her work in decision theory involves finding such necessary conditions, investigating the admissiblity properties of various estimatiors for problems arising from biology, genetics and fishery.

Currently,  she is interested in applied statistical problems related to clinical and translational research.

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