Estimation and model selection of semiparametric multivariate survival functions under general censorship.
We study estimation and model selection of semiparametric models of multivariate survival functions for censored data, which are characterized by possibly misspecified parametric copulas and nonparametric marginal survivals. We obtain the consistency and root-nasymptotic normality of a two-step copula estimator to the pseudo-true copula parameter value according to KLIC, and provide a simple consistent estimator of its asymptotic variance, allowing for a first-step nonparametric estimation of the marginal survivals. We establish the asymptotic distribution of the penalized pseudo-likelihood ratio statistic for comparing multiple semiparametric multivariate survival functions subject to copula misspecification and general censorship. An empirical application is provided.
Cowles Foundation for Research in Economics, Yale University, Box 208281, New Haven, CT 06520, USA.
Xiaohong
X
Chen
Department of Economics, Vanderbilt University, VU Station B 351819, 2301 Vanderbilt Pl., Nashville, TN 37235, USA.
Yanqin
Y
Fan
Department of Economics, New York University, 19 West 4th Steet, 6FL, New York, NY 10012, USA.
Demian
D
Pouzo
Department of Statistics, Columbia University, 1255 Amsterdam Avenue, 10FL, New York, NY 10027, USA.
Zhiliang
Z
Ying
Fixed or random censoring; Kaplan–Meier estimator; Misspecified copulas; Multivariate survival models; Penalized pseudo-likelihood ratio