AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random variables, then they are normally distributed with zero means and equal variances if and only if R is independent of (Θ1, …, Θn−1), R and Θ1, …, Θn−1 being the corresponding spherical coordinates. It is shown below that if (X1, …, X8) and (X8+1, …, Xn) are two independent random vectors having a continuous joint density function which is nonzero, then X1, …, Xn are independent and normally distributed with zero means and equal variances if and only if for some integer l ∈ {1, …, n−1}, (R, Θ1, …, Θl−1) and (Θl, …, Θn−1) are independent
AbstractSeveral general results are presented whereby various properties of independence or conditio...
AbstractLet Gn denote the empirical distribution based on n independent uniform (0, 1) random variab...
AbstractA simple direct proof is given of a result due to L. Shepp that a certain function of two in...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
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...
AbstractLet Xj = (X1j ,…, Xpj), j = 1,…, n be n independent random vectors. For x = (x1 ,…, xp) in R...
AbstractIt is the purpose of this paper to show that, when X and Y are independent normal random var...
AbstractIt is the purpose of this note to provide a direct proof of the fact that, when X and Y are ...
AbstractLet n denote the sample size, and let ri ∈ {1,…,n} fulfill the conditions ri − ri−1 ≥ 5 for ...
AbstractLet Xj (j = 1,…,n) be i.i.d. random variables, and let Y′ = (Y1,…,Ym) and X′ = (X1,…,Xn) be ...
Let X be a random vector on and let R = [short parallel]X[short parallel] and for R [not equal to] 0...
AbstractIn this paper, it is shown that two random matrices have a joint matrix variate normal distr...
AbstractLet Y be an N(μ, Σ) random variable on Rm, 1 ≤ m ≤ ∞, where Σ is positive definite. Let C be...
AbstractIt is shown that when the random vector X in Rn has a mean and when the conditional expectat...
AbstractSeveral general results are presented whereby various properties of independence or conditio...
AbstractLet Gn denote the empirical distribution based on n independent uniform (0, 1) random variab...
AbstractA simple direct proof is given of a result due to L. Shepp that a certain function of two in...
AbstractTamhankar [2] showed that, under suitable conditions, if X1, …, Xn are independent random va...
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...
AbstractLet Xj = (X1j ,…, Xpj), j = 1,…, n be n independent random vectors. For x = (x1 ,…, xp) in R...
AbstractIt is the purpose of this paper to show that, when X and Y are independent normal random var...
AbstractIt is the purpose of this note to provide a direct proof of the fact that, when X and Y are ...
AbstractLet n denote the sample size, and let ri ∈ {1,…,n} fulfill the conditions ri − ri−1 ≥ 5 for ...
AbstractLet Xj (j = 1,…,n) be i.i.d. random variables, and let Y′ = (Y1,…,Ym) and X′ = (X1,…,Xn) be ...
Let X be a random vector on and let R = [short parallel]X[short parallel] and for R [not equal to] 0...
AbstractIn this paper, it is shown that two random matrices have a joint matrix variate normal distr...
AbstractLet Y be an N(μ, Σ) random variable on Rm, 1 ≤ m ≤ ∞, where Σ is positive definite. Let C be...
AbstractIt is shown that when the random vector X in Rn has a mean and when the conditional expectat...
AbstractSeveral general results are presented whereby various properties of independence or conditio...
AbstractLet Gn denote the empirical distribution based on n independent uniform (0, 1) random variab...
AbstractA simple direct proof is given of a result due to L. Shepp that a certain function of two in...