Let f be an infinitely divisible characteristic function without normal factor. We establish some sufficient conditions for f to belong to the class of characteristic functions without indecomposable factor. These conditions concern the support of the measure appearing in the Lévy-Khintchine...

For testing the independence of q-sets in a p-variate normal population, the asymptotic distributions of the likelihood ratio test, and the test proposed by the author under local alternatives are derived in terms of noncentral [chi]2 variates.

The vector sum of a white noise in an unknown hyperspace and an Ornstein-Uhlenbeck process in an unknown line is observed through sharp linear test functions over a finite time span. The parameters associated with the white noise (including the hyperplane) are determinable with precision and...

Functionals of Brownian motion can be dealt with by realizing them as functionals of white noise. Specifically, for quadratic functionals of Brownian motion, such a realization is a powerful tool to investigate them. There is a one-to-one correspondence between a quadratic functional of white...

Canonical correlation analysis is shown to be equivalent to the problem of estimating a linear regression matrix, B0, of less than full rank. After reparameterizing B0 some estimates of the new parameters, obtained by solving an eigenvalue problem and closely related to canonical correlations...

The paper consists of two parts. The first part deals with solutions to some optimization problems. The general problem is one of minimssing Tr AVA'U, where V and U are positive definite matrices when the elements of the matrix are subject to linear restrictions of the type AX = O or X'AX = O...

Given independent samples from three multivariate populations with cumulative distribution functions F(1)(x), F(2)(x), and F(0)(x) = [theta]F(1)(x) + (1 - [theta])F(2)(x), where 0 = [theta] = 1 is unknown, the three-action problem involving decision as to whether the value of [theta] is high,...

If W and Z are independent random vectors and Y1, Y2, ..., Yn are the result of a transformation satisfying certain general conditions then W and Z are distributed according to a certain class of densities if and only if for suitable q, (Y1, ..., Yq) and (Yq+1, ..., Yn) are independent.