Overview
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.
Full Product Details
Author: Mayer Alvo ,
Philip L.H. Yu
Publisher: Springer-Verlag New York Inc.
Imprint: Springer-Verlag New York Inc.
Edition: 2014 ed.
Dimensions:
Width: 15.50cm
, Height: 1.80cm
, Length: 23.50cm
Weight: 6.083kg
ISBN: 9781493914708
ISBN 10: 1493914707
Pages: 273
Publication Date: 03 September 2014
Audience:
College/higher education
,
Undergraduate
,
Postgraduate, Research & Scholarly
Format: Hardback
Publisher's Status: Active
Availability: Manufactured on demand
We will order this item for you from a manufactured on demand supplier.
Reviews
The book is written at the level of a research monograph and is best suited for senior undergraduate and graduate students. The procedures are often illustrated by applications to real data sets. ... the volume can very well serve as a textbook for courses on statistical methods for ranking data. (Lucia Santamaria, zbMATH 1341.62001, 2016) This book is essentially a compilation of several research results contributed by the authors and their collaborators to the area of statistical analysis of ranking data. ... This book is suitable for researchers and analysts in various domains like web commerce, health analytics, and so on, where invariably there is lot of data for analysis and inference. The two facets presented in the book, nonparametric statistics and modeling, offer valuable tools for analysis and inference. (Laxminarayana Pillutla, Computing Reviews, May, 2015)
This book is essentially a compilation of several research results contributed by the authors and their collaborators to the area of statistical analysis of ranking data. This book is suitable for researchers and analysts in various domains like web commerce, health analytics, and so on, where invariably there is lot of data for analysis and inference. The two facets presented in the book, nonparametric statistics and modeling, offer valuable tools for analysis and inference. (Laxminarayana Pillutla, Computing Reviews, May, 2015)
