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.

Sequential Estimation of the Ratio of Scale Parameters in the Exponential Two-sample Problem

Abstract: We consider a sequential point estimation of the ratio of two exponential scale parameters. For a fully sequential sampling scheme, second order approximations are obtained to the expected sample size and the risk of the sequential procedure. We also propose a bias-corrected procedure to reduce the risk.

A better probability model for the racetrack using Beyer speed numbers

Abstract: The dominant model in research related to the racetrack is that a horse's probability of winning a race is equal to the fraction of the win pool bet on that horse when adjusted for a favorite long-shot bias. A new model is developed using Beyer speed numbers to estimate the probability of a horse winning a race. An SPRT like test is developed to determine which of these two models is better. Although developed for the racetrack, this SPRT like test can be utilized whenever there are two models for assigning probabilities and the better model needs to be selected.

Truncated Sequential Non-Parametric Hypothesis Testing Based on Random Distortion Testing

Abstract: In this paper, we propose a new algorithm for sequential non-parametric hypothesis testing based on Random Distortion Testing (RDT). The data-based approach is non-parametric in the sense that the underlying signal distributions under each hypothesis are assumed to be unknown. Our previously proposed non-truncated sequential algorithm, Seq RDT, was shown to achieve desired error probabilities under a few assumptions on the signal model. In this paper, we show that the proposed truncated sequential algorithm, T- Seq RDT, requires even fewer assumptions on the signal model, while guaranteeing the error probabilities to be below pre-specified levels and at the same time makes a decision faster compared to its optimal fixed-sample-size counterpart, Block RDT. We derive bounds on the error probabilities and the average stopping times of the algorithm. Via numerical simulations, we compare the performance of T- Seq RDT with Seq RDT, Block RDT, sequential probability ratio test, and composite sequential probability ratio tests. We also show the robustness of the proposed approach compared with the standard likelihood ratio based approaches.

A New Multiple Hypothesis Tracker Integrated with Detection Processing.

Abstract: In extant radar signal processing systems, detection and tracking are carried out independently, and detected measurements are utilized as inputs to the tracking procedure. Therefore, the tracking performance is highly associated with detection accuracy, and this performance may severely degrade when detections include a mass of false alarms and missed-targets errors, especially in dense clutter or closely-spaced trajectories scenarios. To deal with this issue, this paper proposes a novel method for integrating the multiple hypothesis tracker with detection processing. Specifically, the detector acquires an adaptive detection threshold from the output of the multiple hypothesis tracker algorithm, and then the obtained detection threshold is employed to compute the score function and sequential probability ratio test threshold for the data association and track estimation tasks. A comparative analysis of three tracking algorithms in a clutter dense scenario, including the proposed method, the multiple hypothesis tracker, and the global nearest neighbor algorithm, is conducted. Simulation results demonstrate that the proposed multiple hypothesis tracker integrated with detection processing method outperforms both the standard multiple hypothesis tracker algorithm and the global nearest neighbor algorithm in terms of tracking accuracy.

A sequential procedure for deciding among three hypotheses

Abstract: Abraham Wald developed the Sequential Probability Ratio Test in the 1940's to perform simple vs. simple hypothesis tests that would control both Type I and Type II error rates. Some applications require a test of three hypotheses. In addition, to perform a simple vs. composite two-sided test, a three-hypothesis test with all hypotheses simple has been suggested. Methods have been proposed that will test three hypotheses sequentially. They range widely in simplicity andaccuracy. In this paper,approximate probabilities of error for Armitage's (1947) test arederived. A method of adjusting the error rates used to establish the decision boundaries in order to attain the nominal error rates is developed.The procedure is compared to existing ones by Monte-Carlo simulation