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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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Journal ArticleDOI
TL;DR: The focus of the paper is on the design of space-time codes for a general multiple-input, multiple-output detection problem, when multiple observations are available at the receiver, and the figure of merit used for optimization purposes is the Kullback-Leibler divergences between the densities of the observations under the two hypotheses.
Abstract: The focus of the paper is on the design of space-time codes for a general multiple-input, multiple-output detection problem, when multiple observations are available at the receiver. The figure of merit used for optimization purposes is the convex combination of the Kullback-Leibler divergences between the densities of the observations under the two hypotheses, and different system constraints are considered. This approach permits to control the average sample number (i.e., the time for taking a decision) in a sequential probability ratio test and to asymptotically minimize the probability of miss in a likelihood ratio test: the solutions offer an interesting insight in the optimal transmit policies, encapsulated in the rank of the code matrix, which rules the amount of diversity to be generated, as well as in the power allocation policy along the active eigenmodes. A study of the region of achievable divergence pairs, whose availability permits optimization of a wide range of merit figures, is also undertaken. A set of numerical results is finally given, in order to analyze and discuss the performance and validate the theoretical results.

28 citations

Book ChapterDOI
TL;DR: In this paper, the authors exploit the sequential multiple decision procedures (SMDP) theory, which generalizes the standard two-hypotheses tests to consider multiple alternative hypotheses, and develop a single, genome-wide test that simultaneously partitions all markers into signal and noise groups, with tight control over both type I and type II errors.
Abstract: As the preceding chapters illustrate, now that whole-genome scan analyses are becoming more common, there is considerable disagreement about the best way to balance between false positives and false negatives (traditionally called type I and type II errors in the statistical parlance). Type I and type II errors can be simultaneously controlled, if we are willing to let the sample size of analysis vary. This is the secret that Wald 1947 discovered in the 1940s that led to the theory of sequential sampling and was the inspiration for Newton Morton in developing the lod score method. We can exploit this idea further and capitalize on an old, but nearly forgotten theory: sequential multiple decision procedures (SMDP) Bechhoffer, et al. 1968, which generalizes the standard “two-hypotheses” tests to consider multiple alternative hypotheses. Using this theory, we can develop a single, genome-wide test that simultaneously partitions all markers into “signal” and “noise” groups, with tight control over both type I and type II errors ( Province, 2000 ). Conceiving this approach as an analysis tool for fixed sample design (instead of a true sequential sampling scheme), we can let the data decide at which point we should move from the hypothesis generation phase of a genome scan (where multiple comparisons make the interpretation of p values and significance levels difficult and controversial), to a true hypothesis-testing phase (where the problem of multiple comparison of multiple comparison has been all but eliminated so that p values may be accepted at face value.

28 citations

Book ChapterDOI
01 Jan 1985
TL;DR: The purpose of this first chapter is the presentation of the main concepts and tools which are used for on-line detection of model changes, in the simplest case, namely jumps in mean.
Abstract: The purpose of this first chapter is the presentation of the main concepts and tools which are used for on-line detection of model changes, in the simplest case, namely jumps in mean. As far as possible, the intuitive aspects of the methods will be emphasized, and the next chapters will be introduced.

28 citations

Journal ArticleDOI
TL;DR: The presented method can improve the accuracy of the sequential probability ratio test by reducing the false and missed alarm probabilities caused by improper model parameters.
Abstract: The sequential probability ratio test is widely used in in-situ monitoring, anomaly detection, and decision making for electronics, structures, and process controls However, because model parameters for this method, such as the system disturbance magnitudes, and false and missed alarm probabilities, are selected by users primarily based on experience, the actual false and missed alarm probabilities are typically higher than the requirements of the users This paper presents a systematic method to select model parameters for the sequential probability ratio test by using a cross-validation technique The presented method can improve the accuracy of the sequential probability ratio test by reducing the false and missed alarm probabilities caused by improper model parameters A case study of anomaly detection of resettable fuses is used to demonstrate the application of a cross validation method to select model parameters for the sequential probability ratio test

27 citations

Journal ArticleDOI
TL;DR: In this article, a class of sequential tests based on robust rank order statistics is developed for one and two sample location problems, and the proposed tests terminate with probability one for square integrable score functions.
Abstract: In this paper, for the one and two sample location problems, a class of sequential tests based on robust rank order statistics is developed. The proposed tests terminate with probability one for square integrable score functions. Under more stringent regularity conditions and for local alternatives, the OC and ASN of the proposed tests are obtained, and the allied asymptotic relative efficiency results with respect to the sequential probability ratio and likelihood ratio tests are studied.

27 citations


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