Statistical Methods for Ranking Data

Häftad, Engelska, 2016

AvMayer Alvo,Philip L.H. Yu,Philip L. H. Yu

1 509 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt för medlemmar vid köp för minst 249 kr.

Finns i fler format (1)

Inbunden

1 779 kr

Skickas inom 10-15 vardagar

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.

Produktinformation

Utgivningsdatum2016-09-17
Mått155 x 235 x 16 mm
Vikt441 g
FormatHäftad
SpråkEngelska
SerieFrontiers in Probability and the Statistical Sciences
Antal sidor273
FörlagSpringer-Verlag New York Inc.
ISBN9781493947812

Tillhör följande kategorier

Matematisk statistik inom Naturvetenskap och teknik
Affärsapplikationer inom Data och IT
Databaser inom Data och IT
Systemvetenskap och AI inom Data och IT

Introduction.- Exploratory Analysis of Ranking Data.- Correlation Analysis of Paired Ranking Data.- Testing for randomness, agreement and interaction.- Block Designs.- General Theory of Hypothesis Testing.- Testing for Ordered Alternatives.- Probability Models for Ranking Data.- Probit Models for Ranking Data.- Decision Tree Models for Ranking Data.- Extension of Distance-Based Models for Ranking Data.- Appendix A: Ranking Data Sets.- Appendix B: Limit Theorems.- Appendix C: Review on Decision Trees.

"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)