Asymptotic Properties of Semiparametric Maximum Likelihood Estimator in Normal Transformation Models for Bivariate Survival Data (Technical Report)

In this technical report, we resort to the modern empirical process theory to study the asymptotic properties of the semiparametric maximum likelihood estimator in normal transformation models for bivariate survival data. We prove that the semiparametric maximum likelihood estimators exist, are consistent and asymptotically normal, and reach the semiparametric efficiency bound, under the semiparametric normal transformation model.