Statistical Inference for Models with Multivariate t-Distributed Errors
This book summarizes the results of various models under normal theory with a brief review of the literature. Statistical Inference for Models with Multivariate t-Distributed Errors:
- Includes a wide array of applications for the analysis of multivariate observations
- Emphasizes the development of linear statistical models with applications to engineering, the physical sciences, and mathematics
- Contains an up-to-date bibliography featuring the latest trends and advances in the field to provide a collective source for research on the topic
- Addresses linear regression models with non-normal errors with practical real-world examples
- Uniquely addresses regression models in Student's t-distributed errors and t-models
- Supplemented with an Instructor's Solutions Manual, which is available via written request by the Publisher
A. K. Md. Ehsanes Saleh, PhD, is Professor Emeritus and Distinguished Research Professor in the School of Mathematics and Statistics at Carleton University, Canada. He has published well-over 200 journal articles, and his research interests include nonparametric statistics, order statistics, and robust estimation. Dr. Saleh is a Fellow of the Institute of Mathematical Statistics, the American Statistical Association, and the Bangladesh Academy of Sciences.
M. Arashi, PhD, is Associate Professor in the Department of Statistics at Shahrood University of Technology, Iran. The recipient of the Award for Teaching Excellence from Shahrood University in 2013, his research interests include shrinkage estimation, distribution theory, and multivariate analysis.
S. M. M. Tabatabaey, PhD, is Associate Professor in the Department of Statistics at Ferdowski University of Mashhad, Iran. The author of over fifteen journal articles, he is also a member of the Institute of Mathematical Statistics and the Iranian Statistical Society.