Stress Affection of Two Scale Truncated Generalized Logistic Parameters with Progressive Censoring

Salma Omar Bleed, Abdallah Mohamed Abdelfattah

Abstract


This paper deals with non-Bayesian estimation problem of constant-stress Accelerated Life Tests (ALTs) when the lifetime of the items follow truncated Generalized Logistic Distribution (GLD). Some considerations on inference based on the use of asymptotically normality of the ML estimators are presented considering the stress effects on the two scale parameters of the truncated GLD with a k-level constant-stress ALT under progressive type-I censored grouped data. The EM algorithm method is used to obtain the estimators of the unknown parameters. In addition, estimator of the two scale parameters, reliability function under usual conditions and Fisher information matrix of the estimators are given. Finally, we present a Simulation Study to illustrate the proposed procedure.


Keywords


Truncated Generalized Logistic Distribution; Constant-stress Accelerated Life Test; EM algorithm method; Fisher Information Matrix; Progressive Type-I Censored Grouped Data

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DOI: http://dx.doi.org/10.18187/pjsor.v13i3.1427

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Title

Stress Affection of Two Scale Truncated Generalized Logistic Parameters with Progressive Censoring

Keywords

Truncated Generalized Logistic Distribution; Constant-stress Accelerated Life Test; EM algorithm method; Fisher Information Matrix; Progressive Type-I Censored Grouped Data

Description

This paper deals with non-Bayesian estimation problem of constant-stress Accelerated Life Tests (ALTs) when the lifetime of the items follow truncated Generalized Logistic Distribution (GLD). Some considerations on inference based on the use of asymptotically normality of the ML estimators are presented considering the stress effects on the two scale parameters of the truncated GLD with a k-level constant-stress ALT under progressive type-I censored grouped data. The EM algorithm method is used to obtain the estimators of the unknown parameters. In addition, estimator of the two scale parameters, reliability function under usual conditions and Fisher information matrix of the estimators are given. Finally, we present a Simulation Study to illustrate the proposed procedure.


Date

2017-09-01

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol. 13 No. 3, 2017



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810