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A sequential sampling plan for the inverse gaussian mean

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Abstract

The inverse gaussian distribution is a flexible model which has been extensively applied in the theory of generalized linear models and accelerated life testing where early failure times predominate. More recently it has received attention in areas such as quality control, and as an underlying model that provides an alternative to the analysis of variance. In reliability testing and acceptance sampling data acquisition is often in the face of scarce resources and may be both costly and time-consuming. In such settings it is desirable to reach a statistically sound decision as quickly as possible. Based on sequential probability ratio tests (SPRT), sequential sampling plans provide one method of arriving at a timely, statistically based decision. A sequential sampling plan for the inverse gaussian process mean when the value of the shape parameter of the density is known is presented in this paper.

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Authors and Affiliations

  1. Computer Information Systems Department, College of Business, Colorado State University, C107 Clark Bldg., 80523, Fort Collins, Colorado, USA

    R. L. Edgeman

  2. Department of Mathematics Faculty of Natural Sciences, University of Puerto Rico, Box of Rio Piedras, 00931, Puerto Rico

    P. M. Salzberg

Authors
  1. R. L. Edgeman
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  2. P. M. Salzberg
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Edgeman, R.L., Salzberg, P.M. A sequential sampling plan for the inverse gaussian mean. Statistical Papers 32, 45–53 (1991). https://doi.org/10.1007/BF02925477

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  • DOI: https://doi.org/10.1007/BF02925477

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