Clustering is one of the most widely used procedures in the analysis of microarray data, for example with the goal of discovering cancer subtypes based on observed heterogeneity of genetic marks between different tissues. It is well known that in such high-dimensional settings, the existence of...

We study in this paper the consistency of Bayesian estimation of a piecewise constant function defined on [0,1] with observations on a grid, using the method in Barron et al. [1999. The consistency of posterior distributions in nonparametric problems. Ann. Statist. 27, 536-561.] In particular,...

We demonstrate the consistency of cross-validation for comparing multiple density estimators using simple inequalities on the likelihood ratio. In nonparametric problems, the splitting of data does not require the domination of test data over the training/estimation data, contrary to Shao [Shao,...

We consider the problem of simultaneous variable selection and estimation in partially linear proportional hazards models when the number of covariates in the linear part diverges with the sample size. We apply the smoothly clipped absolute deviation (SCAD) penalty to select the significant...

We study the problem of estimating time-varying coefficients in ordinary differential equations. Current theory only applies to the case when the associated state variables are observed without measurement errors as presented in Chen and Wu (2008) [4] and [5]. The difficulty arises from the...

We consider the problem of variable selection for the generalized linear models (GLMs) with longitudinal data. An automatic variable selection procedure is developed using smooth-threshold generalized estimating equations (SGEE). The proposed procedure automatically eliminates inactive...

In this short paper, we demonstrate that the popular penalized estimation method typically used for variable selection in parametric or semiparametric models can actually provide a way to identify linear components in additive models. Unlike most studies in the literature, we are NOT performing...

We propose an empirical likelihood method for application to a partially linear panel data model with fixed effects. The empirical log-likelihood ratio statistic is proved to be asymptotically chi-squared distributed, and the asymptotic properties of estimators for both the parametric and...

In this paper, we present an estimation approach based on generalized estimating equations and a variable selection procedure for single-index models when the observed data are clustered. Unlike the case of independent observations, bias-correction is necessary when general working correlation...

In this paper, following the results presented in Liu's work [Liu, A.Y., 2002. Efficient estimation of two seemingly unrelated regression equations. Journal of Multivariate Analysis 82, 445-456], we first represent the Gauss-Markov estimator of the regression parameter as a matrix series, and...