时间：2019年3月19日（周二），上午10:00—11:00
地点：中北校区理科大楼A302
题目：Statistical Analysis of Noise Multiplied Data Using Multiple Imputation
报告人：Professor Bimal Sinha, Department of Mathematics and Statistics, University of Maryland Baltimore County (UMBC)
摘要：
A statistical analysis of data that have been multiplied by randomly drawn noise variables in order to protect the confidentiality of individual values has recently drawn some attention. If the distribution generating the noise variables has low to moderate variance, then noise multiplied data have been shown to yield accurate inferences in several typical parametric models under a formal likelihood based analysis. However, the likelihood based analysis is generally complicated due to the non-standard and often complex nature of the distribution of the noise perturbed sample even when the parent distribution is simple. This complexity places a burden on data users who must either develop the required statistical methods or implement the methods if already available or have access to specialized software perhaps yet to be developed. In this paper we propose an alternate analysis of noise multiplied data based on multiple imputation. Some advantages of this approach are that (1) the data user can analyze the released data as if it were never perturbed, and (2) the distribution of the noise variables does not need to be disclosed to the data user.
报告人简介：
Professor Sinha is the Founder of the Statistics Graduate Program at UMBC.
A 1973 PhD in statistics from the University of Calcutta/India, Professor Sinha is an ex-faculty of the Indian Statistical Institute and the University of Pittsburgh. A Professor of Statistics at UMBC since 1985, Professor Sinha's research activities span topics in theoretical and applied statistics, including multivariate analysis, linear models, ranked set sampling, environmental statistics, statistical meta-analysis, and data analysis under confidentiality protection. He has coedited several volumes, and coauthored four books (John Wiley, Springer, Academic). He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and an elected member of the International Statistical Institute. His research has been funded by the US Environmental Protection Agency for about twenty years.
Professor Sinha's research contribution in the area of environmental statistics has been recognized through a Distinguished Achievement Award from the Environmental Statistics Section of the American Statistical Association. In acknowledgment of his research productivity, Professor Sinha was named a Presidential Research Professor in 2008. Furthermore, he received the University System of Maryland Board of Regents Excellence in Research award in 2012.
Professor Sinha has served on the editorial board of several national and international statistics journals, and mentored over 30 PhD students.