This article considers the practical problem in clinical and observational studies where multiple treatment or prognostic groups are compared and the observed survival data are subject to right censoring. Two possible formulations of multiple comparisons are suggested. Multiple Comparisons with...

The intraclass correlation coefficient (ICC) in a two-way analysis of variance is a ratio involving three variance components. Two recently developed methods for constructing confidence intervals (CI’s) for the ICC are the Generalized Confidence Interval (GCI) and Modified Large Sample (MLS)...

A pair-copula construction is a decomposition of a multivariate copula into a structured system, called regular vine, of bivariate copulae or pair-copulae. The standard practice is to model these pair-copulae parametrically, inducing a model risk, with errors potentially propagating throughout...

Despite its slow convergence, the use of the Bernstein polynomial approximation is becoming more frequent in Statistics, especially for density estimation of compactly supported probability distributions. This is due to its numerous attractive properties, from both an approximation (uniform...

In images with low contrast-to-noise ratio (CNR), the information gain from the observed pixel values can be insufficient to distinguish foreground objects. A Bayesian approach to this problem is to incorporate prior information about the objects into a statistical model. A method for...

Confidence interval construction for the Youden index of a diagnostic test based on partially validated series with dichotomous response is considered in this article. Using the Wald and Agresti-Coull, the Wilson score, logit-transformation and the method of variance estimates recovery, eight...

Approximate Maximum Likelihood Estimation (AMLE) is a simple and general method recently proposed for approximating MLEs without evaluating the likelihood function. The only requirement is the ability to simulate the model to be estimated. Thus, the method is quite appealing for spatial models...

The task of estimating a Gaussian graphical model in the high-dimensional setting is considered. The graphical lasso, which involves maximizing the Gaussian log likelihood subject to a lasso penalty, is a well-studied approach for this task. A surprising connection between the graphical lasso...

In this paper, we study the entropy test for the goodness of fit test in (nonlinear) autoregressive conditional duration (ACD) models. To implement a test, we first explore the null limiting distribution of the residual empirical process from ACD models and verify that it has an asymptotic...

The lasso and its variants have attracted much attention recently because of its ability of simultaneous estimation and variable selection. When some prior knowledge exists in applications, the performance of estimation and variable selection can be further improved by incorporating the prior...