Point and interval estimation under progressive type-I interval censoring with random removal

Article Type

Research Article

Publication Title

Statistical Papers

Abstract

This work considers point and interval estimation based on data from a life test under progressive type-I interval censoring with random removal. The asymptotic properties of the maximum likelihood estimators (MLEs) are established under appropriate regularity conditions. Asymptotic confidence intervals and β-content γ-level tolerance interval are obtained by using the asymptotic normality of MLEs. A simulation study is undertaken to assess the performance of the MLEs, confidence intervals and tolerance interval. Lastly, the minimum sample size required to achieve a desired β-content γ-level tolerance interval is determined.

First Page

445

Last Page

477

DOI

10.1007/s00362-017-0948-y

Publication Date

2-1-2020

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