ISBN: 9781119625391 - rank-based methods for shrinkage and selection: with application to machine learning (7 Ergebnisse)

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. In English.

Zustand: New.

Zustand: New. A. K. Md. Ehsanes Saleh, PhD, is a Professor Emeritus and Distinguished Professor in the School of Mathematics and Statistics, Carleton University, Ottawa, Canada. He is Fellow of IMS, ASA and Honorary member of SSC, Canada.Mohammad Arashi, PhD, is an Assoc.

Hardcover. Zustand: Brand New. 482 pages. 9.17x6.30x1.26 inches. In Stock.

Zustand: New. 2022. 1st Edition. Hardcover. . . . . . Books ship from the US and Ireland.

Buch. Zustand: Neu. Neuware - 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.…