We consider the problem of simultaneous variable selection and estimation in additive partially linear Cox’s proportional hazards models with high-dimensional or ultra-high-dimensional covariates in the linear part. Under the sparse model assumption, we apply the smoothly clipped absolute...

Our goal is to predict a scalar value or a group membership from the discretized observation of curves with sharp local features that might vary both vertically and horizontally. To this aim, we propose to combine the use of the nonparametric functional regression estimator developed by Ferraty...

In this study, a more general single-index regression model was presented to characterize the relationship between a dichotomous response and covariates of interest. With M-phase (M≥2) case-control data supplemented by information on a response and certain covariates, we propose a pseudo...

We study the problem of ergodicity, stationarity and maximum likelihood estimation for multinomial logistic models that include a latent process. Our work includes various models that have been proposed for the analysis of binary and, more general, categorical time series. We give verifiable...

A class of models is considered to describe the data to be collected using a design of experiment. One model within the class will possibly describe the data more adequately than the others which will be the “true model” but we do not know its identification. In the pioneering work of...