Person:
Castilla González, Elena María

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First Name
Elena María
Last Name
Castilla González
URI
https://hdl.handle.net/20.500.14352/75718
Affiliation
Universidad Complutense de Madrid
Faculty / Institute
Ciencias Matemáticas
Department
Estadística e Investigación Operativa
Area
Estadística e Investigación Operativa
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2021 - 20222
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Author: Balakrishnan, Narayanaswamy × Subject: 519.22 ×

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    Divergence-based robust inference under proportional hazards model for one-shot device life-test
    (IEEE Transactions on Reliability, 2021) Balakrishnan, Narayanaswamy; Castilla González, Elena María; Martín, N; Pardo Llorente, Leandro
    In this paper, we develop robust estimators and tests for one-shot device testing under proportional hazards assumption based on divergence measures. Through a detailed Monte Carlo simulation study and a numerical example, the developed inferential procedures are shown to be more robust than the classical procedures, based on maximum likelihood estimators.
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    Power divergence approach for one-shot device testing under competing risks
    (Journal of Computational and Applied Mathematics, 2022) Balakrishnan, Narayanaswamy; Castilla González, Elena María; Martín Apaolaza, Nirian; Pardo Llorente, Leandro
    Most work on one-shot devices assume that there is only one possible cause of device failure. However, in practice, it is often the case that the products under study can experience any one of various possible causes of failure. Robust estimators and Wald-type tests are developed here for the case of one-shot devices under competing risks. An extensive simulation study illustrates the robustness of these divergence-based estimators and test procedures based on them. A data-driven procedure is proposed for choosing the optimal estimator for any given data set which is then applied to an example in the context of survival analysis.