A well known sufficient condition for the mean residual life order of two random variables is the hazard rate order of the two random variables. The hazard rate order is characterized by the monotonicity of the ratio of the two survival functions. However in many cases this ratio is non monotone...

Low-rank smoothing techniques have gained much popularity in non-standard regression modeling. In particular, penalized splines and tensor product smooths are used as flexible tools to study non-parametric relationships among several covariates. The use of standard statistical software...

The generalized persistence (GP) model, developed in the context of estimating “value added” by individual teachers to their students’ current and future test scores, is one of the most flexible value-added models in the literature. Although developed in the educational setting, the GP...

The Sea Surface Temperature (SST) is one of the environmental indicators monitored by buoys of the Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Project. In this work, a year-ahead prediction procedure based on SST knowledge of previous periods is proposed and coupled...

A generalization of the commonly used Maximum Likelihood based learning algorithm for the logistic regression model is considered. It is well known that using the Laplace prior (L1 penalty) on model coefficients leads to a variable selection effect, when most of the coefficients vanish. It is...

Many clinical trials compare the efficacy of K (≥3) treatments in repeated measurement studies. However, the design of such trials has received relatively less attention from researchers. Zhang and Ahn (2012) derived a closed-form sample size formula for two-sample comparisons of time-averaged...

This paper discusses nonparametric comparison of survival functions when one observes only interval-censored failure time data (Peto and Peto, 1972; Sun, 2006; Zhao et al., 2008). For the problem, a few procedures have been proposed in the literature. However, most of the existing test procedures...

A data-driven bandwidth selection method for backfitting estimation of semiparametric additive models, when the parametric part is of main interest, is proposed. The proposed method is a double smoothing estimator of the mean-squared error of the backfitting estimator of the parametric terms....

The maximum rank correlation (MRC) approach is the most common method used in the literature to estimate the regression coefficients in the semiparametric linear transformation regression model. However, the objective function Gn(β) in the MRC approach is not continuous. The optimization of...

In this paper, we study the robust estimation for the covariance matrix of stationary multivariate time series. As a robust estimator, we propose to use a minimum density power divergence estimator (MDPDE) designed by Basu et al. (1998). To supplement the result of Kim and Lee (2011), we employ...