Motivated by regression analysis of censored survival data, we develop herein a general asymptotic distribution theory for estimators defined by estimating equations of the form [summation operator]ni=1[xi] (wi, [theta], Gn) = 0, in which wi represents observed data, [theta] is an unknown...

This paper provides an elementary way to establish the general strong approximation theorems for independent random variables by using two special results of Sakhanenko. Applications to the law of the iterated logarithm and the strong law of large numbers are discussed.

Convergence properties of weighted sums of functions in D([0, 1]; E) (E a Banach space) are investigated. We show that convergence in the Skorokhod J1-topology of a sequence (xn) in D([0, 1]; E) does not imply convergence of a sequence (n) of averages. Convergence in the J1-topology of a...

Moments of generalized Wishart distributions are obtained through tensor differential forms and reindexing.

We consider the problem of estimating a continuous bounded probability density function when independent data X1, ..., Xn from the density are partially contaminated by measurement error. In particular, the observations Y1, ..., Yn are such that P(Yj = Xj) = p and P(Yj = Xj + [epsilon]j) = 1 -...

In this paper we show the asymptotic normality of L1-estimators for nonlinear regression models.

Consider the problem in which we have a sample from each of two multivariate normal populations with equal covariance matrices and we wish to classify a new observation as coming from one of the two populations. It is widely regarded that the most commonly used discriminant procedure for this...

A particular class of tests for the principal components of a scatter matrix [Sigma] is proposed. In the simplest case one wants to test whether a given vector is an eigenvector of [Sigma] corresponding to its largest eigenvalue. The test statistics are likelihood ratio statistics for the...

The lattice conditional independence (LCI) model N() is defined to be the set of all normal distributions N(0, [Sigma]) on I such that for every pair L, M [set membership, variant] , xL and xM are conditionally independent given xL [intersection] M. Here is a ring of subsets (hence a...

It is shown that under natural extreme-value conditions a distributional Bahadur-Kiefer theorem holds in a point lying outside the sample. The limiting distribution is degenerate if the extreme-value index is equal to one; the proper refinement for that case is also established. In both cases the...