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Summary:
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 Frank et al [frank] and Kapur [kapur]. 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.
References:
[1] Csiszár I.: Eine Informationstheoretische Ungleichung und ihre Anwendung auf den Beweis der Ergodizität von Markoffschen Ketten. Publications of the Mathematical Institute of Hungarian Academy of Sciences Ser A. 8 (1963), 85–108 MR 0164374
[2] Dik J. J., Gunst M. C. M. de: The distribution of general quadratic forms in normal variables. Statistica Neerlandica 39 (1985), 14–26 DOI 10.1111/j.1467-9574.1985.tb01121.x | MR 0801686 | Zbl 0591.62043
[3] Eckler A. R.: A survey of coverage problems associated with point and area targets. Technometrics 11 (1969), 561–589 DOI 10.1080/00401706.1969.10490712 | Zbl 0181.22105
[4] Ferguson T. S.: A Course in Large Sample Theory. Chapman & Hall, London 1996 MR 1699953 | Zbl 0871.62002
[5] Frank O., Menéndez M. L., Pardo L.: Asymptotic distributions of weighted divergence between discrete distributions. Comm. Statist. – Theory Methods 27 (1998), 4, 867–885 DOI 10.1080/03610929808832133 | MR 1613493 | Zbl 0902.62025
[6] Fraser D. A. S.: Non–parametrics Methods in Statistics. Wiley, New York 1957 MR 0083868
[7] Guiaşu S.: Grouping data by using the weighted entropy. J. Statist. Plann. Inference 15 (1986), 63–69 DOI 10.1016/0378-3758(86)90085-6 | MR 0864945 | Zbl 0621.62008
[8] Gupta S. S.: Bibliography on the multivariate normal integrals and related topics. Ann. Math. Statist. 34 (1963), 829–838 DOI 10.1214/aoms/1177704005 | MR 0152069
[9] Jensen D. R., Solomon H.: A Gaussian approximation to the distribution of a definite quadratic form. J. Amer. Statist. Assoc. 67 (1972), 340, 898–902 Zbl 0254.62013
[10] Johnson N. L., Kotz S.: Tables of distributions of positive definite quadratic forms in central normal variables. Sankhya, Ser. B 30 (1968), 303–314 MR 0256492
[11] Kapur J. N.: Measures of Information and their Applications. Wiley, New York 1994 Zbl 0925.94073
[12] Kotz S., Johnson N. M., Boid D. W.: Series representation of quadratic forms in normal variables I. Central case. Annals Math. Statist. 38 (1967), 823–837 DOI 10.1214/aoms/1177698877 | MR 0211510
[13] Liese F., Vajda I.: Convex Statistical Distances. Teubner, Leipzig 1987 MR 0926905 | Zbl 0656.62004
[14] Longo G.: Quantitative and Qualitative Measure of Information. Springer, New York 1970 MR 0351627
[15] Menéndez M. L., Morales D., Pardo L., Salicrú M.: Asymptotic behaviour and statistical applications of divergence measures in multinomial populations: A unified study. Statistical Papers 36 (1995), 1–29 DOI 10.1007/BF02926015 | MR 1334081 | Zbl 0846.62004
[16] Menéndez M. L., Morales D., Pardo L., Vajda I.: Approximations to powers of $\varphi $-disparity goodness of fit tests. Submitted
[17] Modarres R., Jernigan R. W.: Testing the equality of correlation matrices. Comm. Statist. – Theory Methods 21 (1992), 2107–2125 DOI 10.1080/03610929208830901 | MR 1186048 | Zbl 0777.62059
[18] Rao J. N. K., Scott A. J.: The analysis of categorical data from complex sample surveys: Chi-squared tests for goodness of fit and independence in two-way tables. J. Amer. Statist. Assoc. 76 (1981), 221–230 DOI 10.1080/01621459.1981.10477633 | MR 0624328 | Zbl 0473.62010
[19] Solomon H.: Distribution of Quadratic Forms – Tables and Applications. Applied Mathematics and Statistics Laboratories, Technical Report 45, Stanford University, Stanford, Calif. 1960
[20] Taneja C. T.: On the mean and the variance of estimates of Kullback information and relative useful information measures. Apl. Mat. 30 (1985), 166–175 MR 0789858 | Zbl 0581.94004
[21] Vajda I.: Theory of Statistical Inference and Information. Kluwer Academic Publishers, Dordrecht 1989 Zbl 0711.62002
[22] Zografos K., Ferentinos K., Papaioannou: $\varphi $ -divergence statistics: sampling properties and multinomial goodness of fit and divergence tests. Comm. Statist. – Theory Methods 19 (1990), 5, 1785-1802 DOI 10.1080/03610929008830290 | MR 1075502
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