About the book
A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications
Theory of Ridge Regression Estimation with Applications 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. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource:
- Offers theoretical coverage and computer-intensive applications of the procedures presented
- Contains solutions and alternate methods for prediction accuracy and selecting model procedures
- Presents the first book to focus on ridge regression and unifies past research with current methodology
- Uses R throughout the text and includes a companion website containing convenient data sets
Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Editions of Theory of Ridge Regression Estimation with Applications
- Hardcover
- ISBN 9781118644614
- EBook
- ISBN 9781118644522
- EBook
- ISBN 9781118644508
- EBook
- ISBN 9781118644478
Read an Excerpt
A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications
Theory of Ridge Regression Estimation with Applications 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. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource:
- Offers theoretical coverage and computer-intensive applications of the procedures presented
- Contains solutions and alternate methods for prediction accuracy and selecting model procedures
- Presents the first book to focus on ridge regression and unifies past research with current methodology
- Uses R throughout the text and includes a companion website containing convenient data sets
Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
Frequently Asked Questions
What is Theory of Ridge Regression Estimation with Applications about?
A guide to the systematic analytical results for ridge, LASSO, preliminary test, and Stein-type estimators with applications
Theory of Ridge Regression Estimation with Applications 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. This book is a volume in the Wiley Series in Probability and Statistics series that provides essential and invaluable reading for all statisticians. This important resource:
- Offers theoretical coverage and computer-intensive applications of the procedures presented
- Contains solutions and alternate methods for prediction accuracy and selecting model procedures
- Presents the first book to focus on ridge regression and unifies past research with current methodology
- Uses R throughout the text and includes a companion website containing convenient data sets
Written for graduate students, practitioners, and researchers in various fields of science, Theory of Ridge Regression Estimation with Applications is an authoritative guide to the theory and methodology of statistical estimation.
What core themes, tropes, or subjects are explored in Theory of Ridge Regression Estimation with Applications?
Mathematics and Science > Mathematics > Probability and statistics
Where can I read a sample of Theory of Ridge Regression Estimation with Applications?
You can read an official preview of the few pages here https://www.book2look.com/book/9781118644614
Is Theory of Ridge Regression Estimation with Applications part of a series, and can it be read as a standalone?
Yes it is a part of series Wiley Series in Probability and Statistics
Who is/are the Author/s of the book Theory of Ridge Regression Estimation with Applications?
A. K. Md. Ehsanes Saleh, B. M. Golam Kibria, Mohammad Arashi
Who is the Publisher of the book Theory of Ridge Regression Estimation with Applications?
Wiley
What are the ISBN numbers for the physical and digital editions?
Theory of Ridge Regression Estimation with Applications is available as hardcover(ISBN 9781118644614) and ebook(ISBN 9781118644522) and ebook(ISBN 9781118644508) and ebook(ISBN 9781118644478)
Where can I buy Theory of Ridge Regression Estimation with Applications online or support local independent bookshops?
You can buy Theory of Ridge Regression Estimation with Applications from below
Where can I buy Theory of Ridge Regression Estimation with Applications?