A Multivariate Log-Linear Model for Birnbaum-Saunders Distributions

Carolina Marchant; Victor Leiva; Francisco Jose A. Cysneiros

doi:10.1109/TR.2015.2499964

A Multivariate Log-Linear Model for Birnbaum-Saunders Distributions

Carolina Marchant, Victor Leiva, Francisco Jose A. Cysneiros

Research output: Contribution to journal › Article › peer-review

48 Scopus citations

Abstract

Univariate Birnbaum-Saunders models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new models with real-world multivariate fatigue data.

Original language	English
Article number	7366614
Pages (from-to)	816-827
Number of pages	12
Journal	IEEE Transactions on Reliability
Volume	65
Issue number	2
DOIs	https://doi.org/10.1109/TR.2015.2499964
State	Published - Jun 2016
Externally published	Yes

Keywords

EM algorithm
Monte Carlo simulation
R software
fatigue data
logarithmic distributions
maximum likelihood method
multivariate generalized Birnbaum-Saunders distributions

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10.1109/TR.2015.2499964

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abstract = "Univariate Birnbaum-Saunders models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new models with real-world multivariate fatigue data.",

keywords = "EM algorithm, Monte Carlo simulation, R software, fatigue data, logarithmic distributions, maximum likelihood method, multivariate generalized Birnbaum-Saunders distributions",

author = "Carolina Marchant and Victor Leiva and Cysneiros, {Francisco Jose A.}",

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AU - Leiva, Victor

AU - Cysneiros, Francisco Jose A.

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AB - Univariate Birnbaum-Saunders models have been widely applied to fatigue studies. Calculation of fatigue life is of great importance in determining the reliability of materials. We propose and derive new multivariate generalized Birnbaum-Saunders regression models. We use the maximum likelihood method and the EM algorithm to estimate their parameters. We carry out a simulation study to evaluate the performance of the corresponding maximum likelihood estimators. We illustrate the new models with real-world multivariate fatigue data.

KW - EM algorithm

KW - Monte Carlo simulation

KW - R software

KW - fatigue data

KW - logarithmic distributions

KW - maximum likelihood method

KW - multivariate generalized Birnbaum-Saunders distributions

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A Multivariate Log-Linear Model for Birnbaum-Saunders Distributions

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Keywords

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