Lower bounds for the expected sample size in the classical and d-posterior statistical problems

I.A. Kareev, I.N. Volodin

Kazan Federal University, Kazan, 420008 Russia

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Abstract

In this report, the problem of construction of lower boundaries for the expected sample size of statistical inference procedures has been considered. The general methodology for construction of the lower bounds and the review of the main results for the classical statistical problems have been presented along with the analysis of the new and earlier results on adoption of the technique to the d-posterior approach. Namely, the hypothesis testing problem has been considered.

Keywords: expected sample size, lower bounds, efficiency, d -posterior approach, Bayesian paradigm, hypothesis testing

Acknowledgements. This work was funded by the subsidy allocated to Kazan Federal University for the state assignment in the sphere of scientific activities (project no. 1.7629.2017/8.9).

The work is performed according to the Russian Government Program of Competitive Growth of Kazan Federal University.

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Received

December 14, 2017

For citation: Kareev I.A., Volodin I.N. Lower bounds for the expected sample size in the classical and d-posterior statistical problems. Uchenye Zapiski Kazanskogo Universiteta. Seriya Fiziko-Matematicheskie Nauki, 2018, vol. 160, no. 2, pp. 309–316. 

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