Semi-parametric inference for semi-varying coefficient panel data model with individual effects

Statistical Inference for Heteroscedastic Semi-Varying Coefficient EV Models.dvi

This paper proposes an estimation procedure for a class of semi-varying coefficient regression models when the covariates of the linear part are subject to measurement errors. Initial estimates for the regression and varying coefficients are first constructed by the profile least squares procedure without input from heteroscedasticity, a bias-corrected kernel estimate for the variance function ...

Estimation of semi-parametric additive coefficient model

In the multivariate regression setting, we propose a flexible varying coefficient model in which the regression coefficients of some predictors are additive functions of other predictors. Marginal integration estimators of the coefficients are developed and their asymptotic properties investigated. Under -mixing, it is found that the estimators of the parameters in the regression coefficients h...

Semi-parametric Inference for Copula Models for Truncated Data

We investigate the dependent relationship between two failure time variables that truncate each other. Chaieb, Rivest, and Abdous (2006) proposed a semiparametric model under the so-called “semi-survival” Archimedean-copula assumption and discussed estimation of the association parameter, the truncation probability, and the marginal functions. Here the same model assumption is adopted but diffe...

Semi-parametric Inference for Copula Models for Dependently Truncated Data

Semi-parametric inferences for association with semi-competing risks data.

In many biomedical studies, it is of interest to assess dependence between bivariate failure time data. We focus here on a special type of such data, referred to as semi-competing risks data. In this article, we develop methods for making inferences regarding dependence of semi-competing risks data across strata of a discrete covariate Z. A class of rank statistics for testing constancy of asso...