Limit distributions of the Pearson statistics for nonhomogeneous polynomial scheme
Diskretnaya Matematika, Tome 29 (2017) no. 4, pp. 121-129.

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For a nonhomogeneous polynomial scheme, conditions are found under which the Pearson statistic distributions converge to the distribution of nonnegative quadratic form of independent random variables with the standard normal distribution.
Keywords: chi-square test, Pearson statistics, limit distributions, noncentral weighted chi-square distribution.
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M. P. Savelov. Limit distributions of the Pearson statistics for nonhomogeneous polynomial scheme. Diskretnaya Matematika, Tome 29 (2017) no. 4, pp. 121-129. http://geodesic.mathdoc.fr/item/DM_2017_29_4_a7/

[1] Kramer G., Matematicheskie metody statistiki, Mir, M., 1975, 648 pp. | MR

[2] Chernoff H., Lehmann E.L., “The use of maximum likelihood estimates in $\chi^2$ tests for goodness of fit”, Ann. Math. Statist., 25:3 (1954), 579–586 | DOI | MR | Zbl

[3] Balakrishnan N., Voinov V., Nikulin M. S., Chi-Squared Goodness of Fit Tests with Applications, Academic Press, 2013, 256 pp. | Zbl

[4] Bulinskii A. V., Shiryaev A. N., Teoriya sluchainykh protsessov, Fizmatlit, M., 2005, 408 pp.

[5] Wang Y. H., “On the number of successes in independent trials”, Statist. Sinica, 3:2 (1993), 295–312 | MR | Zbl

[6] Chanda K. C., “Chi-square goodness-of-fit tests based on dependent observations”, Statistical Distributions in Scientific Work, NATO Adv. Study Inst. Ser., 79, Springer, Dordrecht, 35–49 | MR

[7] Selivanov B. I., “Limit distributions of the $\chi^2$ statistic of K. Pearson in a sequence of independent trials”, Math. Notes, 83:6 (2008), 821–832 | DOI | DOI | MR | Zbl

[8] van der Vaart A. W., Asymptotic statistics, Cambridge Univ. Press, 2000, 445 pp. | MR | Zbl

[9] Solomon H., Stephens M. A., “Distribution of a sum of weighted chi-square variables”, J. Amer. Statist. Assoc., 72:360 (1977), 881–885 | DOI | Zbl

[10] Jensen D. R., Solomon H., “A Gaussian approximation to the distribution of a definite quadratic form”, J. Amer. Statist. Assoc., 67:340 (1972), 898–902 | Zbl