Statistical inference for models with multivariate t-distributed errors / A.K. Md. Ehsanes Saleh, M. Arashi and S.M.M. Tabatabaey.
Material type:
TextPublication details: New Jersey : John Wiley, c2014.Description: xxiv, 248 p. : illustrations ; 25 cmISBN: - 9781118854051 (hardback)
- 000SA.06 23 Sa163
| Item type | Current library | Call number | Status | Date due | Barcode | Item holds | |
|---|---|---|---|---|---|---|---|
| Books | ISI Library, Kolkata | 000SA.06 Sa163 (Browse shelf(Opens below)) | Available | 136202 |
Browsing ISI Library, Kolkata shelves Close shelf browser (Hides shelf browser)
| 000SA.06 K64 Multivariate nonparametric regression and visualization : | 000SA.06 P192 Growth curve modeling : | 000SA.06 P769 Model-free prediction and regression : | 000SA.06 Sa163 Statistical inference for models with multivariate t-distributed errors / | 000SA.06 T136 Learning regression analysis by simulation / | 000SA.061 R873 Graphical models for categorical data / | 000SA.062 Ag277 Foundations of linear and generalized linear models / |
Includes bibliographical references and indexes.
1. Introduction--
2. Preliminaries --
3. Location model --
4. Simple regression model --
5. ANOVA --
6. Parallelism model --
7. Multiple regression model --
8. Ridge regression --
9. Multivariate models --
10. Bayesian analysis --
11. Linear prediction models --
12. Stein estimation--
References--
Author index--
Subject index.
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.
There are no comments on this title.
