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.

Evaluation of detection algorithms for MAC layer misbehavior: theory and experiments

Abstract: We revisit the problem of detecting greedy behavior in the IEEE 802.11 MAC protocol by evaluating the performance of two previously proposed schemes: DOMINO and the sequential probability ratio test (SPRT). Our evaluation is carried out in four steps. We first derive a new analytical formulation of the SPRT that considers access to the wireless medium in discrete time slots. Then, we introduce an analytical model for DOMINO. As a third step, we evaluate the theoretical performance of SPRT and DOMINO with newly introduced metrics that take into account the repeated nature of the tests. This theoretical comparison provides two major insights into the problem: it confirms the optimality of SPRT, and motivates us to define yet another test: a nonparametric CUSUM statistic that shares the same intuition as DOMINO but gives better performance. We finalize the paper with experimental results, confirming the correctness of our theoretical analysis and validating the introduction of the new nonparametric CUSUM statistic.

An Examination of Decision-Theory Adaptive Testing Procedures

Abstract: Rather than make a classification decision (pass/fail, below basic/basic/proficient/advanced) for an individual after administering a fixed number of items, it is possible to sequentially select items to maximize information, update the estimated classification probabilities and then evaluate whether there is enough information to terminate testing. In measurement this is frequently called adaptive or tailored testing. In statistics, this is called sequential testing.

Multi-fault Condition Monitoring of Slurry Pump with Principle Component Analysis and Sequential Hypothesis Test

Abstract: A new method about the multi-fault condition monitoring of slurry pump based on principal component analysis (PCA) and sequential probability ratio test (SPRT) is proposed. The method identifies th...

Early Detection of Signal and Process Anomalies in Enterprise Computing Systems.

Abstract: This paper presents a real-time machine learning technique that has been adapted from the field of statistical process control (SPC) to give early annunciation of incipient anomalies in signals and processes involving enterprise computing systems and associated networks. A binary-hypothesis technique called the sequential probability ratio test (SPRT) provides optimal detection of change points for online surveillance of digitized signals and demonstrates the dual advantages of high sensitivity with good avoidance of false alarms. SPRT-based systems are being developed for a variety of applications to enhance the reliability, availability, and serviceability of enterprise computing systems.

Open-ended tests for Koopman-Darmois families

Abstract: The generalized likelihood ratio is used to define a stopping rule for rejecting the null hypothesis θ = θ0 in favor of θ > θ0. Subject to a bound α on the probability of ever stopping in case θ = θ0, the expected sample sizes for θ > θ0 are minimized within a multiple of log log α-1, the multiple depending on θ. An heuristic bound on the error probability of a likelihood ratio procedure is derived and verified in the case of a normal mean by consideration of a Wiener process. Useful lower bounds on the small-sample efficiency in the normal case are thereby obtained.