Estimation of the Birnbaum-Saunders regression model with current status data

Authors:
Qingchu Xiao;Zaiming Liu;N. Balakrishnan;Xuewen Lu
Affiliations:
School of Mathematical Science and Computing Technology, Central South University, Changsha, Hunan 410075, China and Department of Information, Hunan University of Commerce, Changsha, Hunan 410205 ...;School of Mathematical Science and Computing Technology, Central South University, Changsha, Hunan 410075, China;Department of Mathematics and Statistics, McMaster University, Hamilton, Ontario, L8S 4K1, Canada;Department of Mathematics and Statistics, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
Venue:
Computational Statistics & Data Analysis
Year:
2010

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Abstract

Estimation for the Birnbaum-Saunders (BS) regression model has been discussed by various authors when data are either complete or subject to Type-I or random censoring. But, this problem has not been considered for the case of interval censoring. In this article, we discuss the estimation of a regression model with current status data when the failure times follow the BS distribution. We estimate the parameters by the method of maximum likelihood, and derive the asymptotic distribution of these estimators. The performance of these estimators is then assessed through Monte Carlo simulations for different sample sizes under two types of monitoring. Finally, an analysis of real data is used to illustrate the proposed method.