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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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TL;DR: The objective of the present work is to develop a novel, non-parametric, sequential decision strategy to decide whether the component is in normal or abnormal conditions that takes into account the quantified uncertainty on the reconstructions in the form of Prediction Intervals (PIs).
8 citations
11 Dec 2014
TL;DR: In this paper, the authors proposed online PV fault diagnosis by using Sequential Probability Ratio Test (SPRT) for improving measured signal value and anomaly detection, which can detect anomaly condition in-situ, and improve making decision for residual signal.
Abstract: Online monitoring of PV performance is prevalent in household application and fault supervisory system is new expectation of home user investors. In this regards, this paper has proposed Online PV fault Diagnosis by using Sequential Probability Ratio Test (SPRT) for improve measured signal value and anomaly detection. To identify defect characteristic of PV system, voltage and current of PV system are measured online and compared with simulated values, then residual signal is generated. SPRT let us to detect anomaly condition in-situ, and improve making decision for residual signal. With investigating of two residual signal of current and voltage, fault diagnosis procedure is suggested to classify types of fault and eventually find probability of fault location.
8 citations
TL;DR: In this paper, the authors consider the construction of sequential tests by means of the familiar linear signed-rank statistics and derive a functional limit theorem for two-sample linear rank statistics and heuristically derived the concept of Pitman efficiency in the sequential case.
Abstract: Let X1, X2,... be a sequence of independent and identically distributed random variables (i.i.d.r.v.) with a continuous distribution function (d.f.) F. For testing the hypothesis of symmetry several non-parametric sequential tests have been proposed. We shall mention only a few articles which are next in spirit to the present paper. Assuming Lehmann alternatives Weed, Bradley and Govindarajulu (1974) constructed an invariant sequential probability ratio test (SPRT). No approximations to the operating characteristic (OC) or the average sample number (ASN) seem to be known. Sen and Ghosh (1974), motivated by a procedure by Cox, developed a general class of sequential signed-rank tests for the location model. Limiting expressions for the OCand the ASN-curve are derived and asymptotic relative efficiencies are computed. Nevertheless, these tests suffer from two drawbacks. First, at every stage an unknown parameter has to be estimated. Second, the kind of Wiener approximation applied requires an increasing initial sample size. Modifying the Pyke-Shorack technique, Braun (1976) proved a functional limit theorem for two-sample linear rank statistics and heuristically derived the concept of Pitman efficiency in the sequential case. Hall and Loynes (1977) extended Le Cain's theory to a sequential analysis setting, presented applications to various tests and announced further results in this direction. Meanwhile the present author learnt from a yet unpublished paper by Lai (1977) in which a sequential version of the classical PitmanNoether theorem together with a uniform functional limit theorem and a result on certain large deviation probabilities have been derived. In this paper we consider the construction of sequential tests by means of the familiar linear signed-rank statistics. Along with the preliminary notations SPRT-type tests and some of their properties are studied in Section 2. In Section 3 the necessary distribution theory is derived. This includes a Chernoff-Savage representation cf. Sen and Ghosh (1973) and Sen (1975), and a "uniform"
8 citations
01 Jan 2006
8 citations