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Bibliographic Details
Main Authors: Castilla, E., Chocano, P. J.
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2506.10152
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author Castilla, E.
Chocano, P. J.
author_facet Castilla, E.
Chocano, P. J.
contents This paper presents a robust method for estimating copula models to evaluate dependence between failure modes in one-shot devices-systems designed for single use and destroyed upon activation. Traditional approaches, such as maximum likelihood estimation (MLE), often produce unreliable results when faced with outliers or model misspecification. To overcome these limitations, we introduce a divergence-based estimation technique that enhances robustness and provides a more reliable characterization of the joint failure-time distribution. Extensive simulation studies confirm the robustness of the proposed method. Additionally, we illustrate its practical utility through the analysis of a real-world dataset.
format Preprint
id arxiv_https___arxiv_org_abs_2506_10152
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Robust copula estimation for one-shot devices with correlated failure modes
Castilla, E.
Chocano, P. J.
Methodology
This paper presents a robust method for estimating copula models to evaluate dependence between failure modes in one-shot devices-systems designed for single use and destroyed upon activation. Traditional approaches, such as maximum likelihood estimation (MLE), often produce unreliable results when faced with outliers or model misspecification. To overcome these limitations, we introduce a divergence-based estimation technique that enhances robustness and provides a more reliable characterization of the joint failure-time distribution. Extensive simulation studies confirm the robustness of the proposed method. Additionally, we illustrate its practical utility through the analysis of a real-world dataset.
title Robust copula estimation for one-shot devices with correlated failure modes
topic Methodology
url https://arxiv.org/abs/2506.10152