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 testing for exponential and pareto distributions

Abstract: This paper deals with the exact calculation of the decision boundaries for sequential probability ratio test for simple hypotheses and alternatives in the case of an exponential or a Pareto distribution. The calculations also enable one to give some idea of the mean sample size for the sequential test.

Some Sequential Procedures for Selecting the Better Bernoulli Treatment by Using a Matched Samples Design

Abstract: The problem of selecting the better Bernoulli treatment by using a matched samples design is considered in the framework of the indifference-zone approach. In Tamhane (1980) a fixed sample procedure (FSP) for this problem was proposed. Here three sequential procedures are considered: (a) a curtailed sampling procedure (CSP), (b) a procedure based on the Wald sequential probability ratio test (SPRT), and (c) a procedure based on the 2-SPRT proposed by Lorden (1976). Comparisons are made between these procedures based on their expected total (tied and untied) sample sizes. It is pointed out that the CSP is the only closed procedure (in terms of the total number of observations) among the three. In addition, for any parameter configuration, the CSP is at least as efficient as the FSP, whereas the SPRT and 2-SPRT can be less efficient than the FSP when success probabilities of the treatments are close. Thus the CSP is a useful practical procedure.

On sequential rank tests

Abstract: Publisher Summary This chapter discusses sequential rank tests. It reviews some properties of the sample distribution function. The non-linear renewal theorem is used to determine the asymptotic distribution of the excess over the boundary. The chapter describes a sequential probability ratio test.

Sequential sampling plans for spruce budworm (Lepidoptera: Tortricidae) egg mass density using Monte Carlo simulation.

Abstract: Sequential sampling plans based on the negative binomial distribution were developed for egg mass density of spruce budworm, Choristoneura fumiferana (Clemens), in Michigan's Upper Peninsula. Plans developed were modifications of Wald's sequential probability ratio test (SPRT) based on Monte Carlo simulation. Parameters of the negative binomial distribution were estimated by the maximum likelihood method. Sampling models developed classify egg mass populations into low and high categories using the number of egg masses on whole branch samples of balsam fir, Abies balsamifera (L.) Voss. Plans are presented for three pairs of population density hypotheses to give forest pest managers the flexibility to select a plan that best meets management objectives. Monte Carlo estimates indicated that Wald's average sample number (ASN) and operating characteristic (OC) equations underestimated the actual ASN values, and the actual alpha and beta error probabilities were smaller than the values prescribed by Wald's equations. Errors were sufficiently large to have serious economic implications during implementation of plans developed from Wald's approximate procedure. The sequential plans developed by modifying the decision boundaries of Wald's SPRT using the Monte Carlo procedure had error probabilities, OC functions, and ASN values that were approximately equal to those desired.