TY  - GEN
AU  - Saleh,A.K.MdEhsanes
AU  - Arashi,Mohammd
AU  - Kibria,B.M.Golam
TI  - Theory of ridge regression estimation with applications
T2  - Wiley Series in Probability and Statistics
SN  - 9781118644614
U1  - 000SA.06 23
PY  - 2019///
CY  - New Jersey
PB  - Wiley
KW  - Statistics
KW  - Regression Analysis
KW  - Ridge Regression Estimation
N1  - Includes bibliographical references and index; 1. Introduction to Ridge regression -- 2. Location and simple linear models -- 3. ANOVA model -- 4. Seemingly unrelated simple linear models -- 5. Multiple linear regression models -- 6. Ridge regression in theory and applications -- 7. Partially linear regression models -- 8. Logistic regression model -- 9. Regression model -- 9. Regression models with autoregressive errors -- 10. Rank-based shrinkage estimation -- 11. High dimensional Ridge regression -- 12. Applications: neural networks and big data
N2  -  This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. It offers a comprehensive guide to the theory and methods of estimation. Ridge regression and LASSO are at the center of all penalty estimators in a range of standard models that are used in many applied statistical analyses. Written by noted experts in the field, the book contains a thorough introduction to penalty and shrinkage estimation and explores the role that ridge, LASSO, and logistic regression play in the computer intensive area of neural network and big data analysis.

Designed to be accessible, the book presents detailed coverage of the basic terminology related to various models such as the location and simple linear models, normal and rank theory-based ridge, LASSO, preliminary test and Stein-type estimators.
The authors also include problem sets to enhance learning
ER  -