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This paper describes importance sampling techniques for Monte Carlo computation of the error probabilities and false alarm rates of sequential GLR (generalized likelihood ratio) tests and detection rules. It also discusses asymptotically optimal choice of the proposal distributions for importance sampling and gives numerical comparisons of the sequential GLR procedures with other sequential tests of composite hypotheses and detection rules in the literature.
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Chan et al. (2005) studied this question.
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