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2002•Journal of the Royal Statistical Society Series B (Statistical Methodology)Requires access

Powerful Goodness-of-fit Tests Based on the Likelihood Ratio

Jin Zhang

Open publisher page 229 citations

Abstract

Summary A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

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What this paper is about

Summary A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

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OpenAlex reports 229 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Summary A new approach of parameterization is proposed to construct a general goodness-of-fit test. It can not only generate traditional tests (including the Kolmogorov–Smirnov, Cramér–von Mises and Anderson–Darling tests) but also produce new types of omnibus tests, which are generally much more powerful than the old ones.

Key concepts: Goodness of fit, Anderson–Darling test, Omnibus test, Mathematics, Statistics, Construct (python library), Kolmogorov–Smirnov test, Statistical hypothesis testing

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