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Kybernetika 41(6):677-698, 2005.

On the Optimal Number of Classes in the Pearson Goodness-of-fit Tests

Domingo Morales, Leandro Pardo and Igor Vajda


Abstract:

An asymptotic local power of Pearson chi-squared tests is considered, based on convex mixtures of the null densities with fixed alternative densities when the mixtures tend to the null densities for sample sizes $n\rightarrow \infty .$ This local power is used to compare the tests with fixed partitions $\mathcal{P}$ of the observation space of small partition sizes $|\mathcal{P}|$ with the tests whose partitions $\mathcal{P}=\mathcal{P}_{n}$ depend on $n$ and the partition sizes $|\mathcal{P}_{n}|$ tend to infinity for $n\rightarrow \infty $. New conditions are presented under which it is asymptotically optimal to let $|\mathcal{P}|$ tend to infinity with $n$ or to keep it fixed, respectively. Similar conditions are presented under which the tests with fixed $|\mathcal{P}|$ and those with increasing $|\mathcal{P}_{n}|$ are asymptotically equivalent.


Keywords: Pearson goodness-of-fit test; Pearson-type goodness-of-fit tests; asymptotic local test power; asymptotic equivalence of tests; optimal number of classes;


AMS: 62G10; 62G20;


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BIB TeX

@article{kyb:2005:6:677-698,

author = {Morales, Domingo and Pardo, Leandro and Vajda, Igor },

title = {On the Optimal Number of Classes in the Pearson Goodness-of-fit Tests},

journal = {Kybernetika},

volume = {41},

year = {2005},

number = {6},

pages = {677-698}

publisher = {{\'U}TIA, AV {\v C}R, Prague },

}


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