Topic
Sequential probability ratio test
About: Sequential probability ratio test is a research topic. Over the lifetime, 1248 publications have been published within this topic receiving 22355 citations.
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TL;DR: In this paper, the idea of step-up and step-down methods for multiple comparisons to sequential designs was extended for testing multiple hypotheses, resulting in a statistical decision for each individual test and controlling the family-wise error rate and the familywise power.
38 citations
TL;DR: In this article, the problem of testing statistical hypothesis in nonlinear regression models with inequality constraints on the parameters is considered, and it is shown that the distribution of the Kuhn-Tucker, the likelihood ratio and the Wald test statistics converges to the same mixture of chi-square distributions under the null hypothesis.
38 citations
TL;DR: In this article, a simple scanning rule based on a cyclic application of a sequential probability ratio test (SPRT) is proposed for a multi-channel system in which one apparatus makes a sequence of observations, one at a time.
Abstract: We consider a multi-channel system in which one apparatus makes a sequence of observations, one at a time. By means of scanning, i.e. selecting a channel to be analyzed at any instant and deciding to stop at some stage, it is required to determine the channel in which there is the signal with prescribed constraints on error probabilities. A simple scanning rule, based on a cyclic application of a sequential probability ratio test (SPRT) is proposed for this problem. It is proved that in the case of Brownian motion, the expected scanning time of this rule is equal to the one of the optimal scanning rule (which is known only for this case). The simple structure of this rule permits to obtain corrected Brownian approximations for its characteristics in the case of exponential family of distributions. The same procedure is used in multi-channel change point problem.
38 citations
09 May 1995
TL;DR: A modified SPRT algorithm is described, using a new feature dubbed blanking variability (BV) as the basis for discrimination, and preliminary results showed that the proposed method decreases the overall error rate to 5%.
Abstract: We describe a modified sequential probability ratio test (SPRT) for the discrimination of ventricular fibrillation (VF) from ventricular tachycardia (VT) in measured surface electrocardiograms. The algorithm uses a novel regularity measure dubbed blanking variability (BV) applied to threshold crossings from the measured ECG. Blanking variability corresponds to the normalized rate of change of cardiac rate as the blanking interval is varied. The algorithm has been trained and tested using separate subsets drawn from the MIT-BIH malignant arrhythmia database. BV values are modeled using a truncated Gaussian distribution, and parameter values are derived by averaging over the training component of the database. In testing, the algorithm achieved an overall classification accuracy of 95%.
37 citations
TL;DR: In this article, the authors exploit the tools of differential geometry to provide a clear explanation for the finite sample lack of invariance of the Wald statistic to algebraically equivalent reformulations of the null hypothesis.
Abstract: In this paper we exploit the tools of differential geometry to provide a clear explanation for the finite sample lack of invariance of the Wald statistic to algebraically equivalent reformulations of the null hypothesis
37 citations