Functional data are infinite-dimensional statistical objects which pose significant challenges to both theorists and practitioners. Both parametric and nonparametric regressions have received attention in the functional data analysis literature. However, the former imposes stringent constraints...

In this paper, we investigate the Bingham distribution when the dimension p is large. Our approach is to use a series expansion of the distribution from which truncation points can be determined yielding particular errors. A point of comparison with the approach of Dryden (2005) is highlighted.

This article deals with linear prediction in large dimensions. One obtains various explicit forms of the best linear predictor in a Hilbert space. The difficulty comes from the fact that the associated linear operator is, in general, not continuous. Applications to ARMAH processes, models with...

We study the estimation of some linear functionals which are based on an unknown lifetime distribution. The observations are assumed to be generated under the semi-parametric random censorship model (SRCM), that is, a random censorship model where the conditional expectation of the censoring...

In this paper, we consider the estimation problem of a correlation coefficient between unobserved variables of interest. These unobservable variables are distorted in a multiplicative fashion by an observed confounding variable. Two estimators, the moment-based estimator and the direct plug-in...

Identified vector autoregressive (VAR) models have become widely used on time series data in recent years, but finite sample inference for such models remains a challenge. In this study, we propose a conjugate prior for Bayesian analysis of normalized VAR models. Under the prior, the marginal...

Consider a linear regression model with both quantitative and qualitative factors and an k-dimensional response variable y whose components are equicorrelated for each observation. The D-optimal design problem is investigated when the levels of the qualitative factor interact with the...

In this paper, we consider a flexible class of semiparametric varying-coefficient mean residual lifetime (MRL) models that depended on an exposure variable where some effects may be functions of the exposure variables and some may be constants. We develop three-step estimation procedures to...

We examine the rate of decay to the limit of the tail dependence coefficient of a bivariate skew-t distribution. This distribution always displays asymptotic tail dependence. It contains as a special case the usual bivariate symmetric t distribution, and hence is an appropriate (skew) extension....

Under a balanced loss function, we investigate the optimal and minimax prediction of finite population regression coefficient in a general linear regression superpopulation model with normal errors. The best unbiased prediction (BUP) is obtained in the class of all unbiased predictors. The...