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.

Parametrical Recognition Algorithm Synthesis Based on the Sequential Analysis

Abstract: In this paper the results of the theory of sequential analysis applying for some recognition tasks are given

Computing wald criteria for nested hypotheses

Abstract: We present a numerically convenient procedure for computing Wald criteria for nested hypotheses. Similar to Szroeter’s (1983) generalized Wald test, the suggested procedure does not require explicit derivation of the restrictions implied by the null hypothesis and hence its use might eliminate an intricate step in testing linear and nonlinear hypotheses. We show that the traditional Wald test, Szroeter’s (1983) generalized Wald test and our procedure are asymptotically equivalent under H0. A class of nonlinear transformations of the restrictions for which the Wald statistic is asymptotically invariant is discussed. Finally, we illustrate the use of our procedure for testing the common factor restrictions in a dynamic regression model.

Sequential patient recruitment monitoring in multi-center clinical trials

Abstract: We propose Sequential Patient Recruitment Monitoring (SPRM), a new monitoring procedure for patient recruitment in a clinical trial. Based on the sequential probability ratio test using improved stopping boundaries by Woodroofe, the method allows for continuous monitoring of the rate of enrollment. It gives an early warning when the recruitment is unlikely to achieve the target enrollment. The packet data approach combined with the Central Limit Theorem makes the method robust to the distribution of the recruitment entry pattern. A straightforward application of the counting process framework can be used to estimate the probability to achieve the target enrollment under the assumption that the current trend continues. The required extension of the recruitment period can also be derived for a given confidence level. SPRM is a new, continuous patient recruitment monitoring tool that provides an opportunity for corrective action in a timely manner. It is suitable for the modern, centralized data management environment and requires minimal effort to maintain. We illustrate this method using real data from two well-known, multicenter, phase III clinical trials.

Cooperative spectrum sensing via 2-SPRT Based multiple-model hypothesis testing

Abstract: This paper presents a 2-SPRT based multiple-model hypothesis testing approach for cooperative spectrum sensing to detecting unknown signal that may have multiple possible distributions with different structural or parametric uncertainties. The traditional sequential probability ratio test (SPRT) based cooperative sensing scheme is promising, because it is optimal for specified simple hypotheses. However, it may suffer from SPRT's lack of an upper bound on its stopping time, especially in the mis-specified case; moreover, it cannot directly handle the sequential cooperative sensing with modeling uncertainties that may have multiple possible distributions. The proposed 2-SPRT based scheme not only cope with the above problems, but also is in a setting that can provide efficient detection results. Performance of the proposed scheme is evaluated for spectrum sensing in an illustrative scenario. Simulation results demonstrate its detection efficiency compared with the traditional schemes.