Add to ORKGLet X be a random vector on and let R = [short parallel]X[short parallel] and for R [not equal to] 0 let W = W/R. Necessary and sufficient conditions are given for R and W to be independent. If X has a non-singular normal distribution we show that the following three conditions are equivalent. 1. (i) the components of X are independent and identically distributed with 0 means and positive variances. 2. (ii) W is uniformly distributed on the unit sphere. 3. (iii) R and W are independent.isotropic distributions normal distributions spherical distributions characterization of probability distributions
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
In this paper, we look at a simple relationship between a random vector having a continuous distribu...
Let Z1,Z2 and W1,W2 be mutually independent random variables, each Zi following the standard normal ...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
It is well known (see [2], p. 158) that if X and Y are independent random variables with a continuou...
AbstractIt is shown that when the random vector X in Rn has a mean and when the conditional expectat...
In this paper, we look at a simple relationship between a random vector having a continuous distribu...
An in-dimensional random vector X is said to have a spherical distribution if and only if its charac...
AbstractIf W and Z are independent random vectors and Y1, Y2, …, Yn are the result of a transformati...
AbstractIf W and Z are independent random vectors and Y1, Y2, …, Yn are the result of a transformati...
AbstractIt is known that if the statistic Y = Σj=1n(Xj + aj)2 is drawn from a population which is di...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
Let $X$ and $Y$ be two random vectors with values in $\bbfR\sp k$ and $\bbfR\sp \ell$, respectively....
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
In this paper, we look at a simple relationship between a random vector having a continuous distribu...
Let Z1,Z2 and W1,W2 be mutually independent random variables, each Zi following the standard normal ...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
It is well known (see [2], p. 158) that if X and Y are independent random variables with a continuou...
AbstractIt is shown that when the random vector X in Rn has a mean and when the conditional expectat...
In this paper, we look at a simple relationship between a random vector having a continuous distribu...
An in-dimensional random vector X is said to have a spherical distribution if and only if its charac...
AbstractIf W and Z are independent random vectors and Y1, Y2, …, Yn are the result of a transformati...
AbstractIf W and Z are independent random vectors and Y1, Y2, …, Yn are the result of a transformati...
AbstractIt is known that if the statistic Y = Σj=1n(Xj + aj)2 is drawn from a population which is di...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
Let $X$ and $Y$ be two random vectors with values in $\bbfR\sp k$ and $\bbfR\sp \ell$, respectively....
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
The paper provides a way to model axially symmetric random fields defined over the two-dimensional u...
In this paper, we look at a simple relationship between a random vector having a continuous distribu...
Let Z1,Z2 and W1,W2 be mutually independent random variables, each Zi following the standard normal ...