Faculty of Business Administration
Do Banks Price Director Reputation? Evidence from Corporate Financial Frauds
Professor of Statistics
Department of Mathematics
Southern University of Science and Technology
In this paper, we propose a new multivariate Laplace distribution from normal variance mixture models, called as Type II multivariate Laplace distribution. Unlike the multivariate Laplace distribution proposed by Eltoft (2006) that all components must have the same value for the mixing variate, the random components in the new distribution could have different value for its own mixing variate and are correlated only through the dependence structure of the normal random vector. Thus, it contains the multiplication of iid univariate Laplace distributions as a special case if the normal covariance matrix is diagonal. A tractable stochastic representation (SR) is used to derive the probability density function and other statistical properties. The maximum likelihood estimates of parameters via an ECM algorithm and the Bayesian methods are derived. Some simulation studies are conducted to evaluate the performance of the proposed methods. Applications in two real data sets indicate that the Type II multivariate Laplace distribution could have a better performance and is distinct from the original one.
Date: Jun 3, 2019 (Monday)
Guo-Liang Tian, Ph.D., is a Full Professor of Statistics at Department of Mathematics of Southern University of Science and Technology (SUSTech). He was an Associate Professor of Statistics at Department of Statistics and Actuarial Science of the University of Hong Kong during 2008-2016. He was a senior bio-statistician at the University of Maryland Greenebaum Cancer Center (Baltimore, Maryland, USA) from 2002 to 2008, a Postdoctoral Research Associate at Department of Biostatistics, St. Jude Children’s Research Hospital (Memphis, Tennessee, USA) from 2000 to 2002, and a Postdoctoral Fellowship at Department of Probability and Statistics, Peking University (Beijing, P.R. China) from 1998 to 2000. He earned his Ph.D. in statistics in 1998 from the Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing. He was an Elected Member of International Statistics Institute. His current research interests include biostatistics, social statistics and computational statistics. He was the author of 14 top tier biostatistics papers and more than 90 other statistics papers in peer-reviewed international academic journals.
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