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DOUBLE STAGE BAYES SHRINKAGE ESTIMATION OF SCALE PARAMETER OF WEIBULL DISTRIBUTION UNDER DIFFERENT LOSS FUNCTIONS USING PROGRESSIVE TYPE II CENSORED SAMPLE

Ashok Shanubhogue

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Abstract

In this paper, we propose double stage Bayes shrinkage estimators for the scale parameter of the Weibull distribution, when the shape parameter is known, using type II progressive censored sample and study their properties under Squared Error Loss Function (SELF) and LINEX Loss Function (LLF). The results show that the suggested estimators, in terms relative risk with respect both SELF and LLF, have better performance than the single stage ML estimator.

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What this paper is about

In this paper, we propose double stage Bayes shrinkage estimators for the scale parameter of the Weibull distribution, when the shape parameter is known, using type II progressive censored sample and study their properties under Squared Error Loss Function (SELF) and LINEX Loss Function (LLF). The results show that the suggested estimators, in terms relative risk with respect both SELF and LLF, have better performance than the single stage ML estimator.

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Available abstract

In this paper, we propose double stage Bayes shrinkage estimators for the scale parameter of the Weibull distribution, when the shape parameter is known, using type II progressive censored sample and study their properties under Squared Error Loss Function (SELF) and LINEX Loss Function (LLF). The results show that the suggested estimators, in terms relative risk with respect both SELF and LLF, have better performance than the single stage ML estimator.

Key concepts: Weibull distribution, Shrinkage estimator, Estimator, Scale parameter, Statistics, Shape parameter, Mathematics, Bayes' theorem

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DOUBLE STAGE BAYES SHRINKAGE ESTIMATION OF SCALE PARAMETER OF WEIBULL DISTRIBUTION UNDER DIFFERENT LOSS FUNCTIONS USING PROGRESSIVE TYPE II CENSORED SAMPLE — Research Paper | ScholarLens