Accelerated Failure Time Models with Log-concave Errors
Ruixuan Liu and
Zhengfei Yu
Tsukuba Economics Working Papers from Faculty of Humanities and Social Sciences, University of Tsukuba
Abstract:
We study accelerated failure time (AFT) models in which the survivor function of the additive error term is log-concave. The log-concavity assumption covers large families of commonly-used distributions and also represents the aging or wear-out phenomenon of the baseline duration. For right-censored failure time data, we construct semi-parametric maximum likelihood estimates of the finite dimensional parameter and establish the large sample properties. The shape restriction is incorporated via a nonparametric maximum likelihood estimator (NPMLE) of the hazard function. Our approach guarantees the uniqueness of a global solution for the estimating equations and delivers semiparametric efficient estimates. Simulation studies and empirical applications demonstrate the usefulness of our method.
Date: 2019-11
New Economics Papers: this item is included in nep-ecm and nep-ore
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://pepp.hass.tsukuba.ac.jp/RePEc/2019-003.pdf (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:tsu:tewpjp:2019-003
Access Statistics for this paper
More papers in Tsukuba Economics Working Papers from Faculty of Humanities and Social Sciences, University of Tsukuba Contact information at EDIRC.
Bibliographic data for series maintained by Yoshinori Kurokawa ().