An asymptotic optimal design.
Rekab, Kamel (1991)
Journal of Applied Mathematics and Stochastic Analysis
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Displaying similar documents to “Transitivity and approximate transitivity in problems of optimal stopping”
An asymptotic optimal design.
Optimal sequential procedures with Bayes decision rules
Andrey Novikov (2010)
Kybernetika
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In this article, a general problem of sequential statistical inference for general discrete-time stochastic processes is considered. The problem is to minimize an average sample number given that Bayesian risk due to incorrect decision does not exceed some given bound. We characterize the form of optimal sequential stopping rules in this problem. In particular, we have a characterization of the form of optimal sequential decision procedures when the Bayesian risk includes both the loss...
On a Stopping Rule for a Class of Sequential Decision Problems.
R. Theodorescu, D. Kalin (1983)
Metrika
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On some minimax sequential decision problems with partial observability
Elżbieta Ferenstein (1985)
Banach Center Publications
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Sequential classification in the case of many populations
M. Krzyśko (1984)
Applicationes Mathematicae
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Some problems in sequential analysis
John A. Bather (1985)
Banach Center Publications
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Optimal sequential multiple hypothesis tests
Andrey Novikov (2009)
Kybernetika
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This work deals with a general problem of testing multiple hypotheses about the distribution of a discrete-time stochastic process. Both the Bayesian and the conditional settings are considered. The structure of optimal sequential tests is characterized.
A class of stopping rules for fixed precision sequential estimates
R. Zieliński (1982)
Applicationes Mathematicae
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On the approximation of some optimal sequential plan
R. Różański (1988)
Applicationes Mathematicae
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Optimal stopping of a sequence of maxima over an unobservable sequence of maxima
K. Szajowski (1984)
Applicationes Mathematicae
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The Bayes sequential estimation of a normal mean from delayed observations
Alicja Jokiel-Rokita (2006)
Applicationes Mathematicae
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The problem of estimating the mean of a normal distribution is considered in the special case when the data arrive at random times. Certain classes of Bayes sequential estimation procedures are derived under LINEX and reflected normal loss function and with the observation cost determined by a function of the stopping time and the number of observations up to this time.