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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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Proceedings Article
01 Jan 2003
TL;DR: In this paper, the design of sequential detection tests under memory constraints is studied and the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory.
Abstract: Sequential tests outperform fixed sample size tests by requiring fewer samples on average to achieve the same level of error performance. The sequential probability ratio test (SPRT) has been suggested by Wald (1947) for sequential binary hypothesis testing problems. SPRT recursively calculates the likelihood of an observed data stream and requires this likelihood to be stored in memory between samples. In this paper we study the design of sequential detection tests under memory constraints. We derive the optimal sequential test in the case where only a quantized version of the likelihood can be stored in memory. An application of the proposed techniques is large scale sensor networks where price and communication constraints dictate limited complexity devices, which store and transmit concise representations of the state of nature.

5 citations

Journal ArticleDOI
TL;DR: Through simulations and theoretical derivations, it is demonstrated that the SPRT on average requires fewer samples to be measured to have comparable Type I and Type II error rates as the current fixed-sample binomial test.

5 citations

Journal ArticleDOI
TL;DR: This paper compared the performance of the frequentist sequential method, specifically, Maximized Sequential Probability Ratio Test (MaxSPRT), and a Bayesian sequential method using simulations and a real world vaccine safety example and considers the proposed Bayesiansequential approach to be a promising alternative for vaccine safety surveillance.
Abstract: With rapid development of computing technology, Bayesian statistics have increasingly gained more attention in various areas of public health. However, the full potential of Bayesian sequential methods applied to vaccine safety surveillance has not yet been realized, despite acknowledged practical benefits and philosophical advantages of Bayesian statistics. In this paper, we describe how sequential analysis can be performed in a Bayesian paradigm in the field of vaccine safety. We compared the performance of the frequentist sequential method, specifically, Maximized Sequential Probability Ratio Test (MaxSPRT), and a Bayesian sequential method using simulations and a real world vaccine safety example. The performance is evaluated using three metrics: false positive rate, false negative rate, and average earliest time to signal. Depending on the background rate of adverse events, the Bayesian sequential method could significantly improve the false negative rate and decrease the earliest time to signal. We consider the proposed Bayesian sequential approach to be a promising alternative for vaccine safety surveillance.

5 citations

Journal ArticleDOI
TL;DR: This paper derives exact critical values for CMaxSPRT, as well as statistical power and expected time to signal, for both continuous and group sequential analysis, and for different rejection boundaries.
Abstract: Sequential analysis is now commonly used for post-market drug and vaccine safety surveillance, and a Poisson stochastic process is typically used for rare adverse events. The conditional maximized ...

5 citations

Sun, Xu, Li, Rangwei, Hu, Peng 
01 Jan 2016
TL;DR: In this paper, a tracking filter algorithm based on the maneuvering detection delay is presented in order to solve the fuzzy problem of target maneuver decision introduced by the measure?ment errors of active sonar.
Abstract: A tracking filter algorithm based on the maneuvering detection delay is presented in order to solve the fuzzy problem of target maneuver decision introduced by the measure?ment errors of active sonar. When the maneuvering detection is unclear, two target moving hypotheses, the uniform and the maneuver, derived from the method of multiple hypothesis tracking, are generated to delay the final decision time. Then the hypothesis test statistics is constructed by using the residual sequence. The active sonar?s tracking ability of unknown prior information targets is improved due to the modified sequential probability ratio test and the integration of the advantages of strong tracking filter and the Kalman filter. Simulation results show that the algorithm is able to not only track the uniform targets accurately, but also track the maneuvering targets steadily. The effectiveness of the algorithm for real underwater acoustic targets is further verified by the sea trial data processing results.

5 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20236
202223
202129
202023
201929
201832