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Selecting a Component with Longer Mean Life Time in Bivariate Pareto Models

Selecting a Component with Longer Mean Life Time in Bivariate Pareto Models
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摘要 In any parallel system, selecting a component with longer mean lifetime is of interest to the researchers. Hanagal (1997) [1] discussed selection procedures for a two-component system with bivariate exponential (BVE) models. In this paper, the problem of selecting a better component with reference to its mean life time under bivariate Pareto (BVP) models is considered. Three selection procedures based on sample proportions, sample means and maximum likelihood estimators (MLE) are proposed. The probability of correct selection for the proposed procedures is evaluated through Monte Carlo simulation using normal approximation. The asymptotic relative efficiency (ARE) of the proposed procedures is presented to facilitate the evaluation of the performance of procedures. In any parallel system, selecting a component with longer mean lifetime is of interest to the researchers. Hanagal (1997) [1] discussed selection procedures for a two-component system with bivariate exponential (BVE) models. In this paper, the problem of selecting a better component with reference to its mean life time under bivariate Pareto (BVP) models is considered. Three selection procedures based on sample proportions, sample means and maximum likelihood estimators (MLE) are proposed. The probability of correct selection for the proposed procedures is evaluated through Monte Carlo simulation using normal approximation. The asymptotic relative efficiency (ARE) of the proposed procedures is presented to facilitate the evaluation of the performance of procedures.
出处 《Open Journal of Statistics》 2015年第5期355-359,共5页 统计学期刊(英文)
关键词 ASYMPTOTIC Relative Efficiency (ARE) BETTER COMPONENT BIVARIATE PARETO Probability of CORRECT Selection Asymptotic Relative Efficiency (ARE) Better Component Bivariate Pareto Probability of Correct Selection
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