Optimal design and performance evaluation of sequentially planned hypothesis tests
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In this paper, we propose a method of construction of optimal sequentially planned tests. In particular, for independent and identically distributed observations we obtain the form of optimal sequentially planned tests which turn to be a particular case of sequentially planned probability ratio tests (SPPRTs). Formulas are given for computing the numerical characteristics of general SPPRTs, like error probabilities, average sampling cost, etc. A numerical method of designing the optimal tests and evaluation of the performance characteristics is proposed, and computer algorithms of its implementation are developed. For a particular case of sampling from a Bernoulli population, the proposed method is implemented in R programming language, the code is available at a public GitHub repository. The proposed method is compared numerically with other known sampling plans.
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