2002Birkhäuser Boston eBooksRequires access

Partitioning the Pearson-Fisher Chi-Squared Goodness-of-Fit Statistic

G.D. Rayner

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Abstract

This paper presents an overview of Rayner and Best’s ( 1989 ) categorised Neyman smooth goodness-of-fit score tests, along with an explanation of recent work into how these tests can be used to construct components of the Pearson-Fisher chi-squared test statistic in the presence of unknown nuisance parameters. A short simulation study examining the size of these component test statistics is also presented.

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What this paper is about

This paper presents an overview of Rayner and Best’s ( 1989 ) categorised Neyman smooth goodness-of-fit score tests, along with an explanation of recent work into how these tests can be used to construct components of the Pearson-Fisher chi-squared test statistic in the presence of unknown nuisance parameters. A short simulation study examining the size of these component test statistics is also presented.

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Available abstract

This paper presents an overview of Rayner and Best’s ( 1989 ) categorised Neyman smooth goodness-of-fit score tests, along with an explanation of recent work into how these tests can be used to construct components of the Pearson-Fisher chi-squared test statistic in the presence of unknown nuisance parameters. A short simulation study examining the size of these component test statistics is also presented.

Key concepts: Pearson's chi-squared test, Goodness of fit, Statistics, Statistic, Mathematics, Chi-square test, Test statistic, Statistical hypothesis testing

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