Consider the class of linear models (with uncorrelated observation, each having variance [sigma]2), in which it is known that at most k (location) parameters are negligible, but it is not known which are negligible. The problem is to identify the nonnegligible parameters. In this paper, for k =...

A process which has just one jump, and whose time parameter is the positive quadrant [0, [infinity]] - [0, [infinity]], is considered. Following Merzbach, related stopping lines are introduced, and the filtration {t1,t23} considered in this paper is such that, modulo completion, the...

The asymptotic normality of some spectral estimates, including a functional central limit theorem for an estimate of the spectral distribution function, is proved for fourth-order stationary processes. In contrast to known results it is not assumed that all moments exist or that the process is...

Suppose that random factor models with k factors are assumed to hold for m, p-variate populations. A model for factorial invariance has been proposed wherein the covariance or correlation matrices can be written as [Sigma]i = LCiL' + [sigma]i2I, where Ci is the covariance matrix of factor...

The purpose of this paper is to give a characterization of the nonnegative MINQUE estimate for variance components. A similar characterization has been given by Pukelsheim but only in some special cases. The proof presented here uses results from convex programming and emphasizes certain...

This paper is devoted to the asymptotic distribution of estimators for the posterior probability that a p-dimensional observation vector originates from one of k normal distributions with identical covariance matrices. The estimators are based on training samples for the k distributions...

The quantile process of the product-limit estimator (PL-quantile process) in the random censorship model from the right is studied via strong approximation methods. Some almost sure fluctuation properties of the said process are studied. Sections 3 and 4 contain strong approximations of the...

The stochastic integral is introduced with respect to a stochastic process X = (Xs)s[epsilon]V, where V is any general partially ordered set satisfying some mild regularity conditions. As important examples the stochastic integral is constructed with respect to a class of Gaussian processes...

The validity of the one-term Edgeworth expansion is proved for the multivariate mean of a random sample drawn without replacement under a limiting non-latticeness condition on the population. The theorem is applied to deduce the one-term expansion for the univariate statistics which can be...

The well-known Doob-Meyer decomposition of a supermartingale as the difference of a martingale and an increasing process is extended in several ways for two-parameter stochastic processes. In particular, the notion of laplacian is introduced which gives more explicit decomposition for...