Graduate Student, Statistics (Affiliate)
I’m mostly interested in Bayesian statistics. I’ve taken Bayesian course in my Master degree and I’m now taking nonparametric Bayesian course. Bayesian way of thinking is simple and natural, and the discovery of MCMC and development of computer calculation efficiency makes Bayesian statistics popular these years.
Project I’m currently working on includes making predictions on claims cost based on insurance company history data, this is data set is actually given by that insurance company, and this is competition organised by that company. And I’m planning another project for my nonparametric Bayesian course, which will hopefully help me understand the whole picture of nonparametric area better. Nonparametric Bayesian is somewhat abstract, but still has many applications in Biostatistics. Third project I’m going to do is for my another stats course, this is doing some inference based on New York traffic tickets data. The data set has millions of observations, which makes it a little hard to deal with.
I don’t much have much project experience in my Master degree, but I read a lot of papers in some courses. For instance, how to deal with multiple testing, and people sometimes have wrong understanding of p-value.
What’s more, I’m very interested in matrix algebra, and I’m taking linear course this semester, which is considered as one of the hardest course in stat department. Some machine learning methods really require some knowledge in matrix algebra, like PCA. My statistical software is R, I can make many beautiful figures by using ggplot2 package in R.
Department of Statistics, MS in STAT, University of Wisconsin, Madison, May 2016
School of Mathematical Sciences, BS in STAT, Nankai University, China, June, 2015
|Mailing Address||Statistics Department1089 Storrs Road Storrs, CT 06268|