The large-sample theory of sequential tests

Author:

Bartlett M. S.

Abstract

1. The general theory underlying sampling inspection methods introduced during the war under the name of sequential analysis, applicable in cases where the sampling units can be taken serially, has mainly been developed by Wald and is now published (5). The original purpose of the present investigation was to exhibit the main structure of the distributional theory relating to the size of sample required by noting its relationship with the classical ‘random-walk’ problem. Thus in Part I of this paper are derived the distribution and characteristic functions of the absorption time for one-dimensional random-walk theory with constant drift and absorbing barriers. Attention is confined to the asymptotic case of numerous independent displacements, for which it is well known that the unrestricted total displacement becomes Gaussian; the motion may also be treated as continuous. Since these results were obtained Wald has independently given an alternative and more general discussion of this problem((4); see also Tweedie (3)), but the extension here of the method of images used by Chandrasekhar (1) still appears of interest, and has advantages over alternative direct methods of solution for the distribution function involving Fourier expansion (cf. 2).

Publisher

Cambridge University Press (CUP)

Subject

General Mathematics

Cited by 64 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Sequential hypothesis tests for multinomial processing tree models;Journal of Mathematical Psychology;2020-04

2. Detecting and dating structural breaks in functional data without dimension reduction;Journal of the Royal Statistical Society: Series B (Statistical Methodology);2017-10-30

3. Sequential Methods for Clinical Trials;Wiley StatsRef: Statistics Reference Online;2014-12-02

4. A Simulation Approach to Assessing Sampling Strategies for Insect Pests: An Example with the Balsam Gall Midge;PLoS ONE;2013-12-23

5. Sequential analysis methodology for a Poisson GLMM with applications to multicenter randomized clinical trials;Journal of Statistical Planning and Inference;2012-12

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