Multi-stage point estimation of the mean of an inverse Gaussian distribution

In this article, we develop two-stage, three-stage, and accelerated sequential procedures for the point estimation of the mean μ of an inverse Gaussian distribution when the scale parameter λ is unknown. Both minimum risk and bounded risk estimation problems are considered subject to a weighted squa...

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Bibliographic Details
Published inSequential analysis Vol. 38; no. 1; pp. 1 - 25
Main Authors Chaturvedi, Ajit, Bapat, Sudeep R., Joshi, Neeraj
Format Journal Article
LanguageEnglish
Published Philadelphia Taylor & Francis 02.01.2019
Taylor & Francis Ltd
Subjects
Accelerated sequential procedure
bounded risk
Estimating techniques
fatigue life
inverse Gaussian
Inverse Gaussian probability distribution
Mean
minimum risk
point estimation
Risk management
second-order approximations
three-stage procedure
two-stage procedure
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ISSN0747-4946
1532-4176
DOI10.1080/07474946.2019.1574438

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Summary:In this article, we develop two-stage, three-stage, and accelerated sequential procedures for the point estimation of the mean μ of an inverse Gaussian distribution when the scale parameter λ is unknown. Both minimum risk and bounded risk estimation problems are considered subject to a weighted squared error loss function. We aim at controlling the associated risk functions for all three procedures. Second-order approximations are obtained for the proposed procedures.
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ISSN:0747-4946
1532-4176
DOI:10.1080/07474946.2019.1574438