Abstract
In this talk, I will describe the family of mean-mixtures of multivariate normal distributions and establish many of its properties, stochastic representations, moments, distributional shape characteristics, etc. I will also describe a general EM-type algorithm for the likelihood estimation of model parameters. I will then present some empirical results and a real data analysis, through a dataset that has been analyzed well in the literature. Finally, if time permits, I will also describe about some multivariate skewness measures for this family and their use in tests of hypotheses.
Brief Biography
Professor N. Balakrishnan received his PhD from the Indian Institute of Technology - Kanpur in 1981. He has been at McMaster University (Hamilton, Canada) since 1985. He is currently a Distinguished University Professor in the Department of Mathematics and Statistics. He works in different areas of Probability and Statistics including Univariate and Multivariate Distribution Theory, Censoring Methodology, Reliability Theory, Survival Analysis, Nonparametric Statistics, Information Theory and Applied Probability. He has received many national and international honours including Fellow of the Royal Society of Canada, Fellow of the Institute of Mathematical Statistics and Fellow of the American Statistical Association. He has received Honorary Doctorate Degree from National and Kapodistrian University of Athens, Greece, and the Don Owen Award and the Mentoring Award from the American Statistical Association. He serves as the Editor-in-Chief of Communications in Statistics and Mathematical Methods of Statistics, and also serves in the Editorial Board of several other journals of international repute.