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The large-sample theory of sequential tests

Published online by Cambridge University Press:  24 October 2008

M. S. Bartlett
Affiliation:
Queens' CollegeCambridge

Extract

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).

Type
Research Article
Copyright
Copyright © Cambridge Philosophical Society 1946

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References

REFERENCES

(1)Chandrasekhar, S.Rev. Mod. Phys. 15 (1943), 1.CrossRefGoogle Scholar
(2)Fürth, R.Ann. d. Phys. 53 (1917), 177.CrossRefGoogle Scholar
(3)Tweedie, M. C. K.Nature, London, 155 (1945), 453.CrossRefGoogle Scholar
(4)Wald, A.Ann. Math. Statist. 15 (1944), 283.CrossRefGoogle Scholar
(5)Wald, A.Ann. Math. Statist. 16 (1945), 117.CrossRefGoogle Scholar