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Parametric and nonparametric inference for the reliability of copula‐based stress‐strength models
Quality and Reliability Engineering International ( IF 1.718 ) Pub Date : 2020-06-29 , DOI: 10.1002/qre.2694
Bernardo Borba de Andrade; Alex Rodrigues do Nascimento; Pushpa Narayan Rathie

This paper provides a general treatment of statistical inference for the reliability in copula‐based stress‐strength models. Most of the current literature is either focused on specific models that yield clean formulas or restricted to estimation and engineering aspects without addressing statistical inference. We present two general frameworks, one parametric, one nonparametric, for the estimation of the reliability. The parametric methodology is presented under the general framework of estimating equations, mostly as a combination of existing methodologies from the fields of multivariate analysis, reliability, and econometrics, with some new results. The nonparametric methodology is a novel application based on an existing bivariate kernel method combined with Monte Carlo estimation of the reliability without specification of the copula or the margins. We present results from a small simulation study designed to assess the robustness of the methods discussed in terms of model misspecification. We used geotechnical data and data from the Brazilian Household Survey to illustrate the proposed methodologies in the estimation of factors of safety and financial fragility.
更新日期:2020-06-29

 

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