Different concepts of neutrality have been studied in the literature in context of independence properties of vectors of random probabilities, in particular, for Dirichlet random vectors. Some neutrality conditions led to characterizations of the Dirichlet distribution. In this paper we provide...

We present a method for the obtention of the maximal correlation coefficient that extends the simple method given by Papadatos and Xifara (2013). We illustrate our method with the calculation of the maximal correlation between the kth largest order statistics of overlapping samples.

Let {Xk,k∈Z} be a zero mean causal AR(∞) process with parameter Θ∈R∞. A very common fitting procedure is to employ the Yule–Walker equations in connection with the Durbin–Levinson algorithm, which yields the (recursive) sequence of estimators Θ̂m:=(θ̂m,1,…,θ̂m,m)⊤,...

Single-index-coefficient regression models (SICRM) have been proposed and used in the literature for avoiding the “curse of dimensionality”. However, there is no efficient model structure determination methodology for the SICRM. This may cause a tendency to use models that are much larger...

Copulas and their corresponding densities are functions of a multivariate joint distribution and the one-dimensional marginals. Bernstein estimators have been used as smooth nonparametric estimators for copulas and copula densities. The purpose of this note is to study the asymptotic...

This paper investigates the hypothesis testing of a mean vector and covariance matrix for multi-populations in the context of two-step monotone incomplete data drawn from Np+q(μ,Σ), a multivariate normal population with mean μ and covariance matrix Σ. Three null hypotheses are considered,...

Given a random sample from a dependent censored variable (X,δ)=(min(T,C),1(TC)), general formulas are given for possible marginal survival functions of the failure time T and the censoring time C under the assumption that their underlying copula is Archimedean. These formulas are used to...

The conditional autoregressive (CAR) and simultaneous autoregressive (SAR) models both have been used extensively for the analysis of spatial structure underlying lattice data in many areas, such as epidemiology, demographics, economics, and geography. Default Bayesian analyses have been...

Modern day science presents many challenges to data analysts. Advances in data collection provide very large (number of observations and number of dimensions) data sets. In many areas of data analysis an informative task is to find natural separations of data into homogeneous groups,...

This paper first illustrates that a mutual information index detects and ranks dependence of a wide variety of absolutely continuous families, but the popular association and variance reduction indices fail to serve as such “common metrics”. We then elaborate on some theoretical merits of...