Penalized likelihood method can be used for hazard estimation with lifetime data that are right-censored, left-truncated, and possibly with covariates. This thesis consists of three parts. The first two parts address issues in the penalized likelihood method for single event lifetime data, and...

This thesis consists of two parts. In chapter 2, we focus on optimal smoothing with correlated data and chapter 3 is devoted to marginal semiparametric modelling of longitudinal/clustered data. Penalized likelihood method offers versatile smoothing techniques in a variety of stochastic settings,...

Penalized likelihood method can be used for hazard estimation with lifetime data that are right-censored, left-truncated, and possibly with covariates. In this article, we are concerned with more scalable computation of the method and with the derivation and assessment of certain interval...

Smoothing splines via the penalized least squares method provide versatile and effective nonparametric models for regression with Gaussian responses. The computation of smoothing splines is generally of the order "O"("n"-super-3), "n" being the sample size, which severely limits its practical...

Penalized likelihood method is among the most effective tools for nonparametric multivariate function estimation. Recently, a generic computation-oriented asymptotic theory has been developed in the density estimation setting, and been extended to other settings such as conditional density...

Generalized cross-validation (GCV) is a popular method for choosing the smoothing parameter in generalized spline smoothing when there are independent errors with common unknown variance. When data points are replicated, one can choose the smoothing parameter by minimizing one of three...