Rank-Based Methods for Shrinkage and Selection

Rank-Based Methods for Shrinkage and Selection

A practical and hands-on guide to the theory and methodology of statistical estimation based on rank

Robust statistics is an important field in contemporary mathematics and applied statistical methods. Rank-Based Methods for Shrinkage and Selection: With Application to Machine Learning describes techniques to produce higher quality data analysis in shrinkage and subset selection to obtain parsimonious models with outlier-free prediction. This book is intended for statisticians, economists, biostatisticians, data scientists and graduate students.

Rank-Based Methods for Shrinkage and Selection elaborates on rank-based theory and application in machine learning to robustify the least squares methodology. It also includes:

• Development of rank theory and application of shrinkage and selection
• Methodology for robust data science using penalized rank estimators
• Theory and methods of penalized rank dispersion for ridge, LASSO and Enet
• Topics include Liu regression, high-dimension, and AR(p)
• Novel rank-based logistic regression and neural networks
• Problem sets include R code to demonstrate its use in machine learning

Author: A. K. MD Ehsanes Saleh
Publisher: Wiley
Published: 04/12/2022
Pages: 480
Binding Type: Hardcover
Weight: 1.78lbs
Size: 9.00h x 6.00w x 1.06d
ISBN: 9781119625391

About the Author

A. K. Md. EHSANES SALEH, PhD, is a professor emeritus and distinguished research professor in the school of Mathematics and Statistics, Carleton University, Canada. Dr. Saleh is author of Theory of Preliminary Test and Stein-Type Estimation with Applications, and co-author of An Introduction to Probability and Statistics, 2nd Edition, Statistical Inference for Models with Multivariate t-Distributed Errors, and Theory of Ridge Regression Estimation with Applications, all published by Wiley.

M. Arashi, PhD, is an Associate Professor at Shahrood University of Technology, Iran and Extraordinary Professor and C2 rated researcher at University of Pretoria, South Africa. Dr. Arashi is co-author of Statistical Inference for Models with Multivariate t-Distributed Errors and Theory of Ridge Regression Estimation with Applications, both published by Wiley.

Mina Norouzirad, PhD, is Lecturer at Faculty of Mathematical Sciences, Shahrood University of Technology, Iran.