A comparison between empirical likelihood and bootstrap tests for a mean parameter against a series of local alternative hypotheses is made by developing Edgeworth expansions for the power functions of the two tests. For univariate and bivariate cases, practical rules are proposed for choosing...

Given some regularity conditions on the distribution F(·) of a random X1, ..., Xn emanating from a strictly stationary sequence of random variables satisfying a strong mixing condition, it is shown that the sequence of quantile processes {nf(F-1(s))(F-1n(s) - F-1(s)); 0 s 1} behaves like a...

For k normal populations with unknown means [mu]i and unknown variances [sigma]2i, i = 1, ..., k, assume that there are some order restrictions among the means and variances, respectively, for example, simple order restrictions: [mu]1 <= [mu]2 <= ... <= [mu]k and [sigma]21 >= [sigma]22 = ... = [sigma]2k 0. Some properties of maximum...</=>

Consider a random field of real-valued random variables with finite second moment and subject to covariance invariance and finite susceptibility. Under the basic assumption of positive or negative association, asymptotic normality is established. More specifically, it is shown that the joint...

Uniform convergence of probability measures is analyzed by topologizing the space of events. A new characterization of narrow (weak) convergence of probability measures on Polish space is also obtained.

Given a sample of n observations from a density [latin small letter f with hook] on d, a natural estimator of [latin small letter f with hook](x) is formed by counting the number of points in some region surrounding x and dividing this count by the d dimensional volume of . This paper presents...

A class of independent multivariate linear models is considered, having a common parameter matrix [Theta] in their means, but having different covariance matrices. For testing H0:[Theta] = 0, some test procedures are derived, which combine the information from the different models. In the...

A multivariate point process is a random jump measure in time and space. Its distribution is determined by the compensator of the jump measure. By an empirical estimator we understand a linear functional of the jump measure. We give conditions for a nonparametric version of local asymptotic...

A sequence of independent, identically distributed random vectors X1, X2, ... is said to belong to the -normed domain of semi-stable attraction of a random vector Y if there exist diagonal matrices An, constant vectors bn and a sequence (kn)n of natural numbers with kn [upwards double arrow]...

Convolutions of random variables which are either exponential or geometric are studied with respect to majorization of parameter vectors and the likelihood ratio ordering ([greater-or-equal, slanted]lr) of random variables. Let X[lambda], ..., X[lambda]n be independent exponential random...