Rank-Based Methods for Shrinkage and Selection

Rank-Based Methods for Shrinkage and Selection

Author: A. K. Md. Ehsanes Saleh

Publisher: John Wiley & Sons

ISBN: 9781119625391

Category: Mathematics

Page: 480

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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
Rank-Based Methods for Shrinkage and Selection
Language: en
Pages: 480
Authors: A. K. Md. Ehsanes Saleh, Mohammad Arashi, Resve A. Saleh, Mina Norouzirad
Categories: Mathematics
Type: BOOK - Published: 2022-03-22 - Publisher: John Wiley & Sons

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
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Pages: 277
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Type: BOOK - Published: 2016-09-20 - Publisher: Springer

The contributors to this volume include many of the distinguished researchers in this area. Many of these scholars have collaborated with Joseph McKean to develop underlying theory for these methods, obtain small sample corrections, and develop efficient algorithms for their computation. The papers cover the scope of the area, including
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Pages: 1616
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The Handbook for Statistical Genetics is widely regarded as the reference work in the field. However, the field has developed considerably over the past three years. In particular the modeling of genetic networks has advanced considerably via the evolution of microarray analysis. As a consequence the 3rd edition of the
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Pages: 286
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Categories: Computers
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Language: en
Pages: 690
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Categories: Mathematics
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