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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.


Papers
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Proceedings ArticleDOI
14 May 2008
TL;DR: The problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses is considered and a likelihood ratio interval is introduced which accommodates the uncertainty in the pdfs.
Abstract: We consider the problem of sequential hypothesis testing when the exact pdfs are not known but instead a set of iid samples are used to describe the hypotheses. We modify the classical test by introducing a likelihood ratio interval which accommodates the uncertainty in the pdfs. The test finishes when the whole likelihood ratio interval crosses one of the thresholds and reduces to the classical test as the number of samples to describe the hypotheses tend to infinity. We illustrate the performance of this test in a medical image application related to tuberculosis diagnosis. We show in this example how the test confidence level can be accurately determined.

11 citations

Journal ArticleDOI
TL;DR: In this paper, the behavior of the test when an erroneous value is taken for the variance is investigated in two applications: (i) when inferences are to be made about the mean itself, and (ii) when the proportion of the population whose measurements exceed a given constant.
Abstract: The properties of Wald's sequential probability ratio test of a simple hypothesis about the mean of a normal population against a simple alternative are well-known. However, the applicability of the procedure is limited in practice because it requires exact knowledge of the population variance. The behavior of the test when an erroneous value is taken for the variance is investigated in two applications: (i) when inferences are to be made about the mean itself, and (ii) when inferences are to be made about the proportion of the population whose measurements exceed a given constant. Use of the test is discussed for each application when the variance can be restricted a priori to a given, finite interval. In such a situation, it is sometimes possible to apply the Wald test, using an assumed value for the variance. A method for doing this is presented which controls the risks of error and for which approximate bounds on the average sample size are easily found. * This work was carried out at the Sta...

11 citations

Journal ArticleDOI
TL;DR: The effectiveness of the proposed fault detection strategy of vehicle wheel angle signal via long short-term memory network (LSTM) and improved sequential probability ratio test (SPRT) is verified.
Abstract: In order to improve the accuracy of fault detection results, this paper proposes a novel fault detection strategy of vehicle wheel angle signal via long short-term memory network (LSTM) and improved sequential probability ratio test (SPRT). Firstly, a signal estimation method based on data-driven modeling is presented, which fuses the vehicle current status information and adopts the LSTM based on deep learning to estimate the vehicle wheel angle signal. Then, the signal residual sequence is obtained by comparing the estimated wheel angle signal with the measured wheel angle signal. Based on this, the improved SPRT method based on mathematical statistics is used to analyze the signal residual sequence, so as to detect the fault signal timely and accurately. Finally, the accuracy of the estimation results is analyzed under sinusoidal condition, double-lane change condition and sinusoidal sweep frequency condition, and the effectiveness of the fault detection strategy proposed in this paper is further verified under the stuck fault condition and drift fault condition. The results indicate the effectiveness of the proposed fault detection strategy, which is of great significance to improve the safety and reliability of the vehicle.

11 citations


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