Statistical Methods for Ranking Data

You must be logged in to access this title.

Sign up now

Already a member? Log in

Synopsis

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis.This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Book details

Edition:
2014
Series:
Frontiers in Probability and the Statistical Sciences
Author:
Mayer Alvo, Philip L.H. Yu
ISBN:
9781493914715
Related ISBNs:
9781493914708
Publisher:
Springer New York
Pages:
N/A
Reading age:
Not specified
Includes images:
Yes
Date of addition:
2019-08-18
Usage restrictions:
Copyright
Copyright date:
2014
Copyright by:
Springer New York, New York, NY 
Adult content:
No
Language:
English
Categories:
Computers and Internet, Mathematics and Statistics, Nonfiction