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Locally most powerful sequential tests of a simple hypothesis vs. One-sided alternatives for independent observations the sense of Berk [Ann. Statist., 3 (1975), pp. 373-381]) sequential tests in this problem (maximizing
Exact statistical inferences and Monte Carlo method invariant under certain groups of transformations, search constants determining statistical inference can
Locally most powerful sequential tests of a simple hypothesis vs. One-sided alternatives for independent observations the sense of Berk [Ann. Statist., 3 (1975), pp. 373-381]) sequential tests in this problem (maximizing
Exact statistical inferences and Monte Carlo method invariant under certain groups of transformations, search constants determining statistical inference can
Information inequalities for characteristics of group-sequential test with groups of observations of random size© 2016, Allerton Press, Inc.We consider a group-sequential test for testing a simple hypothesis
Locally most powerful sequential tests of a simple hypothesis vs. one-sided alternatives is an open subset of the real line. We consider the problem of testing a simple hypothesis H0: θ = θ0 vs. a
Locally most powerful sequential tests of a simple hypothesis vs. one-sided alternatives is an open subset of the real line. We consider the problem of testing a simple hypothesis H0: θ = θ0 vs. a
Information inequalities for characteristics of group-sequential test with groups of observations of random size© 2016, Allerton Press, Inc.We consider a group-sequential test for testing a simple hypothesis
Asymptotic Expansion of D-Risks for Hypothesis Testing in Bernoulli Scheme-risk of any statistical procedure. In this paper we present the asymptotic expansion of d-risk function
On the statistical methods for the conclusion on the climate change the last 20 years has a slight tendency to increase. However, using the both statistical tests
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