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

Sonal Budhiraja () and Biswabrata Pradhan
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Sonal Budhiraja: Indian Statistical Institute
Biswabrata Pradhan: Indian Statistical Institute

Statistical Papers, 2020, vol. 61, issue 1, No 23, 445-477

Abstract: 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 $$\beta $$β-content $$\gamma $$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 $$\beta $$β-content $$\gamma $$γ-level tolerance interval is determined.

Keywords: Asymptotic normality; Binomial removal; Consistency; Maximum likelihood estimator; Regularity condition; Tolerance interval (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s00362-017-0948-y

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