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Kybernetika 36(5):589-602, 2000.

Goodness of Fit Tests with Weights in the Classes Based on (h, f)-divergences.

Elena Landaburu and Leandro Pardo


Abstract:

The aim of the paper is to present a test of goodness of fit with weigths in the classes based on weighted $\left( h,\phi \right) $-divergences. This family of divergences generalizes in some sense the previous weighted divergences studied by [O. Frank, M.L. Men\'{e}ndez and L. Pardo: Asymptotic distributions of weighted divergence between discrete distributions. Comm. Statist. -- Theory Methods {\mi 27} (1998), 4, 867--885.] and [J.N. Kapur: Measures of Information and their Applications. Wiley, New York 1994.]. The weighted $\left( h,\phi \right)$-divergence between an empirical distribution and a fixed distribution is here investigated for large simple random samples, and the asymptotic distributions are shown to be either normal or equal to the distribution of a linear combination of independent chi-square variables. Some approximations to the linear combination of independent chi-square variables are presented.


AMS: 62C;


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BIB TeX

@article{kyb:2000:5:589-602,

author = {Landaburu, Elena and Pardo, Leandro},

title = {Goodness of Fit Tests with Weights in the Classes Based on (h, f)-divergences.},

journal = {Kybernetika},

volume = {36},

year = {2000},

number = {5},

pages = {589-602}

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

}


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