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.

An Enhanced Source Anonymity Method Framework for Sensor Networks with Replica Detection Using Hypothesis Testing

Abstract: In certain applications, the locations of events reported by a sensor network need to remain anonymous. That is, unauthorized observers must be unable to detect the origin of such events by analyzing the network traffic. Known as the source anonymity problem, this problem has emerged as an important topic in the security of wireless sensor networks, with variety of techniques based on different adversarial assumptions being proposed. This thesis presents a new framework for modeling, analyzing, and evaluating anonymity in sensor networks. The novelty of the proposed framework is twofold: first, it introduces the notion of "interval in distinguish ability" and provides a quantitative measure to model anonymity in wireless sensor networks; second, it maps source anonymity to the statistical problem of binary hypothesis testing with nuisance parameters. The thesis shows how mapping source anonymity to binary hypothesis testing with nuisance parameters leads to converting the problem of exposing private source information into searching for an appropriate data transformation that removes or minimize the effect of the nuisance information. By doing so, it transforms the problem from analyzing real-valued sample points to binary codes, which opens the door for coding theory to be incorporated into the study of anonymous sensor networks. In addition, to mitigate the limitations of previous schemes, the thesis proposes a zone-based node compromise detection scheme in sensor networks. The main idea of the proposed scheme is to use sequential hypothesis testing to detect suspect regions in which compromised nodes are likely placed. A fast and effective mobile replica node detection scheme is proposed using the Sequential Probability Ratio Test.

A primer of reliability theory

Abstract: Reliability distributions multicomponent systems stand-by redundancy life testing the sequential probability ratio test availability and maintainability military standards.

Sequential probability ratio test for zero inflation in counting data

Abstract: In this paper, we will discuss the sequential probability ratio test to test the zero inflation in counting data with the sample size being a random variable with specified Type I and Type II error

Minimum probability of error of list M-ary hypothesis testing

Abstract: We study a variation of Bayesian $M$-ary hypothesis testing in which the test outputs a list of $L$ candidates out of the $M$ possible upon processing the observation. We study the minimum error probability of list hypothesis testing, where an error is defined as the event where the true hypothesis is not in the list output by the test. We derive two exact expressions of the minimum probability or error. The first is expressed as the error probability of a certain non-Bayesian binary hypothesis test and is reminiscent of the meta-converse bound by Polyanskiy, Poor and Verdú (2010). The second, is expressed as the tail probability of the likelihood ratio between the two distributions involved in the aforementioned non-Bayesian binary hypothesis test. Hypothesis testing, error probability, information theory.

Sequential Performance Analysis of Systems that Age and Rejuvenate

Abstract: Sequential performance analysis aims at evaluating performance indicators in an online fashion. The process stops in accordance with a pre-defined stopping rule, as soon as an anomaly that should produce an alarm is observed. Traditional sequential performance analysis techniques include CUSUM and sequential probability ratio test (SPRT). More recent techniques include the bucket algorithm, wherein tokens are accumulated into buckets when the system degrades, and removed when the system naturally recovers. If the number of tokens in the system reaches a threshold, an alarm is triggered. In this paper, we analyze sequential performance analysis algorithms applied to a system that is subject to rejuvenation. Among our results, we indicate how rejuvenation impacts the time until false alarms, and how to set the optimal rejuvenation rate accounting for the fact that systems can recover from transient performance degradation either naturally, as in standard sequential performance analysis models, or due to rejuvenation.