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Chi-squared goodness-of-fit tests fo...

Nikulin, M. S.

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Chi-squared goodness-of-fit tests for censored data

Record Type:	Electronic resources : Monograph/item
Title/Author:	Chi-squared goodness-of-fit tests for censored data/ Mikhail S. Nikulin, Ekaterina V. Chimitova.
Author:	Nikulin, M. S.
other author:	Chimitova, Ekaterina V.
Published:	London, UK :ISTE ; : 2017.,
Description:	1 online resource.
Subject:	Chi-square test. -
Online resource:	https://onlinelibrary.wiley.com/doi/book/10.1002/9781119427605
ISBN:	9781119427605

Chi-squared goodness-of-fit tests for censored data
Nikulin, M. S.

Chi-squared goodness-of-fit tests for censored data[electronic resource] /Mikhail S. Nikulin, Ekaterina V. Chimitova. - 1st ed. - London, UK :ISTE ;2017. - 1 online resource. - Stochastic models in survival analysis and reliability set ;v. 3. - Stochastic models in survival analysis and reliability set ;v. 3..

Includes bibliographical references and index.

This book is devoted to the problems of construction and application of chi-squared goodness-of-fit tests for complete and censored data. Classical chi-squared tests assume that unknown distribution parameters are estimated using grouped data, but in practice this assumption is often forgotten. In this book, we consider modified chi-squared tests, which do not suffer from such a drawback. The authors provide examples of chi-squared tests for various distributions widely used in practice, and also consider chi-squared tests for the parametric proportional hazards model and accelerated failure time model, which are widely used in reliability and survival analysis. Particular attention is paid to the choice of grouping intervals and simulations.This book covers recent innovations in the field as well as important results previously only published in Russian. Chi-squared tests are compared with other goodness-of-fit tests (such as the Cramer-von Mises-Smirnov, Anderson-Darling and Zhang tests) in terms of power when testing close competing hypotheses.

ISBN: 9781119427605

Standard No.: 10.1002/9781119427605doiSubjects--Topical Terms:

2045568
Chi-square test.

LC Class. No.: QA277.3

Dewey Class. No.: 519.5/6

Chi-squared goodness-of-fit tests for censored data
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050 4 $a QA277.3
082 0 4 $a 519.5/6 $2 23
100 1 $a Nikulin, M. S. $q (Mikhail Stepanovich) $3 723806
245 1 0 $a Chi-squared goodness-of-fit tests for censored data $h [electronic resource] / $c Mikhail S. Nikulin, Ekaterina V. Chimitova.
250 $a 1st ed.
260 $a London, UK : $b ISTE ; $a Hoboken, NJ : $b John Wiley & Sons, $c 2017.
300 $a 1 online resource.
490 1 $a Stochastic models in survival analysis and reliability set ; $v v. 3
504 $a Includes bibliographical references and index.
520 8 $a This book is devoted to the problems of construction and application of chi-squared goodness-of-fit tests for complete and censored data. Classical chi-squared tests assume that unknown distribution parameters are estimated using grouped data, but in practice this assumption is often forgotten. In this book, we consider modified chi-squared tests, which do not suffer from such a drawback. The authors provide examples of chi-squared tests for various distributions widely used in practice, and also consider chi-squared tests for the parametric proportional hazards model and accelerated failure time model, which are widely used in reliability and survival analysis. Particular attention is paid to the choice of grouping intervals and simulations.This book covers recent innovations in the field as well as important results previously only published in Russian. Chi-squared tests are compared with other goodness-of-fit tests (such as the Cramer-von Mises-Smirnov, Anderson-Darling and Zhang tests) in terms of power when testing close competing hypotheses.
588 $a Description based on print version record.
650 0 $a Chi-square test. $3 2045568
700 1 $a Chimitova, Ekaterina V. $3 3319179
830 0 $a Stochastic models in survival analysis and reliability set ; $v v. 3. $3 3319180
856 4 0 $u https://onlinelibrary.wiley.com/doi/book/10.1002/9781119427605