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Operating Characteristic and Average Sample Number of Binary and Multi-Hypothesis Sequential Probability Ratio Test

机译:二元和多假设序列概率比检验的操作特性和平均样本数

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摘要

The operating characteristic (OC) and average sample number (ASN) of the sequential probability ratio test (SPRT) and multi-hypothesis SPRT (MSPRT) are studied. We consider the case where the observation sequence is independent but not necessarily identically distributed. Also, the thresholds for the test can be time varying. Based on the governing equations for OC and ASN of the SPRT developed in our previous work, a solution for the general case is proposed. The governing equations for OC and ASN of the MSPRT are also obtained. Numerical solutions for MSPRT are developed. Basically, the solutions rely on approximating the original test by truncation, that is, truncating the test at some finite time . We show that under some mild conditions, the approximation error diminishes as increases, at the cost of increased computation. Numerical examples are provided to demonstrate our solutions by comparing with Monte Carlo simulations, Simon’s lower bound, and Dragalin’s method (if available) for ASN.
机译:研究了顺序概率比检验(SPRT)和多假设SPRT(MSPRT)的操作特性(OC)和平均样本数(ASN)。我们考虑观察序列是独立的但不一定相同分布的情况。同样,测试的阈值可能会随时间变化。基于我们先前工作中开发的SPRT的OC和ASN的控制方程,提出了一般情况的解决方案。还获得了MSPRT的OC和ASN的控制方程。开发了MSPRT的数值解。基本上,解决方案依赖于通过截断近似原始测试,即在某个有限时间截断测试。我们表明,在某些温和条件下,逼近误差随着增加而减小,但以增加计算为代价。通过与Monte Carlo模拟,Simon的下界和Dragalin的ASN方法(如果有)进行比较,提供了一些数字示例来说明我们的解决方案。

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