In this paper we consider the problem of estimating an unknown joint distribution which is defined over mixed discrete and continuous variables. A nonparametric kernel approach is proposed with smoothing parameters obtained from the cross-validated minimization of the estimator's integrated...

For the estimation of coefficients in a measurement error model, the least squares method utilizing original observations and averaged observations over replications provides inconsistent estimators. Based on these, consistent estimators are formulated and asymptotic properties are analyzed.

A new method is developed for estimating the spectral measure of a multivariate stable probability measure, by representing the measure as a sum of spherical harmonics.

We show that a nonparametric estimator of a regression function, obtained as solution of a specific regularization problem is the best linear unbiased predictor in some nonparametric mixed effect model. Since this estimator is intractable from a numerical point of view, we propose a tight...

This paper derives and evaluates an algorithm for estimating normal covariances. A particular concern is the performance of the estimator when the dimension of the space exceeds the number of observations. The algorithm is simple, tolerably well founded, and seems to be more accurate for its...

In this paper, a family of the skew elliptical distributions is defined and investigated. Some basic properties, such as stochastic representation, marginal and conditional distributions, distribution under linear transformations, moments and moment generating function are derived. The joint...

This paper presents a construction of the uniformly minimum variance unbiased (UMVU) estimator of real-valued functions for the simple quadratic natural exponential families on . A polynomial expansion of the estimator is derived and a condition for its existence is given. The exact variance of...

This paper deals with correlation tests from the class of spherical tests introduced by Läuter (Biometrics 52 (1996) 964). These methods provide an alternative to classical MANOVA approaches and are particularly useful in small samples. Following a brief introduction of the spherical tests, it...

We consider large and moderate deviations for the empirical mean and covariance of hilbertian autoregressive processes. As an application we obtain moderate deviations principles for the eigenvalues and associated projectors of the empirical covariance.

This note provides some equivalence results across the partition lattice, the monotypic lattice, and the subset lattice, for decomposing a multivariate density.