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Grouped Dirichlet Distribution (GDD) and Nested Dirichlet Distribution (NDD) : New Tools for Incomplete Categorical Data
澳门新葡8455最新网站:2010年07月06日 00:00 点击数:

报告人:Guo-Liang Tian

报告地点:澳门新葡8455最新网站五楼报告厅(501)

报告澳门新葡8455最新网站:2010年07月15日下午16:00-17:00

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报告摘要:

Motivated by the likelihood functions of incomplete categorical data in different background, we have proposed and developed in a serious of papers with collaborators two new families of distributions as new tools. They are Grouped Dirichlet Distribution and Nested Dirichlet Distribution, both encompassing the classical Dirichlet distribution as a special case. In this talk, we shall separately review the properties of these two families of distributions in their own rights and demonstrate with real and simulated data how these two expanded families of distributions emerge as new tools for both maximum likelihood and Bayesian inference of incomplete categorical data. The advantages of using these new tools will be discussed in detail.

主讲人概况:

Guo-Liang Tian, PHD,Associate Professor of Statistics,Dept of Statistics and Actuarial Sciencem,The University of Hong Kong.

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