Abstract:
Using the machinery of large and moderate deviations theory of empirical probability measures, we study effective importance sampling for simulation of large and moderate deviation probabilities of tests and estimators. The computational burden of efficient importance sampling does not have the exponential growth as in the straightforward simulation. The results are implemented in a simulation of moderate deviation probabilities of tests of omega-squared type.
Keywords:
importance sampling, large deviations, moderate deviations, empirical measure.
Citation:
M. S. Ermakov, “Importance sampling for simulation of large and moderate deviation probabilities of tests and estimators”, Teor. Veroyatnost. i Primenen., 51:2 (2006), 319–332; Theory Probab. Appl., 51:2 (2007), 279–290
\Bibitem{Erm06}
\by M.~S.~Ermakov
\paper Importance sampling for simulation of large and moderate deviation probabilities of tests and estimators
\jour Teor. Veroyatnost. i Primenen.
\yr 2006
\vol 51
\issue 2
\pages 319--332
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\transl
\jour Theory Probab. Appl.
\yr 2007
\vol 51
\issue 2
\pages 279--290
\crossref{https://doi.org/10.1137/S0040585X97982323}
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Linking options:
https://www.mathnet.ru/eng/tvp56
https://doi.org/10.4213/tvp56
https://www.mathnet.ru/eng/tvp/v51/i2/p319
This publication is cited in the following 3 articles:
Kuznetsov N.Yu., Kuznetsov I.N., “Fast Simulation of the Customer Blocking Probability in Queueing Networks With Multicast Access”, Cybern. Syst. Anal., 57:4 (2021), 530–541
Broniatowski M. Caron V., “Long Runs Under a Conditional Limit Distribution”, Ann. Appl. Probab., 24:6 (2014), 2246–2296
Khomyak O.N., “Determination of Probability of Intersection of Trajectory Functionals for Two Markovian Chains by the Method of Significant Sampling”, J. Automat. Inf. Sci., 45:8 (2013), 75–81
Citation in format AMSBIB
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