Add to ORKGIt is well known (see [2], p. 158) that if X and Y are independent random variables with a continuous joint probability density function (pdf) which is spherically symmetric about the origin, then both X and Y are normally distributed. In this note we examine the condition that the joint pdf be spherically symmetric about the origin and show that the normal distribution is strongly dependent on the choice of metric for R2
Abstract. Tractable generalizations of the Gaussian distribution play an important role for the anal...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
The distribution of product of two normally distributed variables come from the first part of the XX...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
A conjecture of Bobkov and Houdré (1995), recently proved by Kwapien et al. (1995), stated that if X...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
AbstractIt is a well known fact that invariance under the orthogonal group and marginal independence...
Let X be a random vector on and let R = [short parallel]X[short parallel] and for R [not equal to] 0...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
A probability distribution is called spherically symmetric if it is invariant with respect to rotati...
An in-dimensional random vector X is said to have a spherical distribution if and only if its charac...
AbstractThe theory of Bayesian least squares is developed for a general and more tangible notion of ...
Let Z1,Z2 and W1,W2 be mutually independent random variables, each Zi following the standard normal ...
AbstractIt is a well known fact that invariance under the orthogonal group and marginal independence...
Abstract. Tractable generalizations of the Gaussian distribution play an important role for the anal...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
The distribution of product of two normally distributed variables come from the first part of the XX...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
A conjecture of Bobkov and Houdré (1995), recently proved by Kwapien et al. (1995), stated that if X...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
AbstractIt is a well known fact that invariance under the orthogonal group and marginal independence...
Let X be a random vector on and let R = [short parallel]X[short parallel] and for R [not equal to] 0...
It is a well known fact that invariance under the orthogonal group and marginal independence uniquel...
A probability distribution is called spherically symmetric if it is invariant with respect to rotati...
An in-dimensional random vector X is said to have a spherical distribution if and only if its charac...
AbstractThe theory of Bayesian least squares is developed for a general and more tangible notion of ...
Let Z1,Z2 and W1,W2 be mutually independent random variables, each Zi following the standard normal ...
AbstractIt is a well known fact that invariance under the orthogonal group and marginal independence...
Abstract. Tractable generalizations of the Gaussian distribution play an important role for the anal...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
The distribution of product of two normally distributed variables come from the first part of the XX...