AbstractThe study is concerned with second-order and fourth-order moments of jointly distributed random matrices. When distributional properties are required, normality is adopted. Some of the results can also be applied to elliptical or Wishart distributions. The developments are entirely algebraic. Full use is made of the Kronecker product, (repeated) vectorization, commutation matrices and related items. There are a few references in the main text but many additional references to other work, in which the same or kindred results (obtained by other methods, procedures or concepts) can be found, have been included in the References
AbstractIn this paper, the authors derived exact expressions for the joint marginal densities of any...
The number of fourth-order moments which can be obtained from a random vector rapidly increases with...
We provide an identity that relates the moment of a product of random variables to the moments of di...
AbstractThe study is concerned with second-order and fourth-order moments of jointly distributed ran...
AbstractA large part of statistics is devoted to the estimation of models from the sample covariance...
AbstractThree results are given involving a normally distributed matrix X, namely (1) the expectatio...
Motivated by recent results in random matrix theory we will study the distributions arising from pro...
AbstractFor a left elliptically contoured n × p random matrix Y LECn × p(μ, K, φ), the mth order mom...
In this paper, we consider the matrix which transforms a Kronecker product of vectors into the avera...
AbstractIn this paper, we consider the matrix which transforms a Kronecker product of vectors into t...
This article derives means, variance--covariance matrices of concomitant vectors corresponding to no...
denotes a Kronecker product. From this, second and third moments of quadratic forms are obtained. Th...
In this paper, we consider the matrix which transforms a Kronecker product of vectors into the avera...
This article provides a comprehensive, rigorous, and self-contained introduction to the analysis of ...
AbstractD. Foata and D. Zeilberger (1988, SIAM J. Discrete Math.4, 425–433) and D. Vere-Jones (1988,...
AbstractIn this paper, the authors derived exact expressions for the joint marginal densities of any...
The number of fourth-order moments which can be obtained from a random vector rapidly increases with...
We provide an identity that relates the moment of a product of random variables to the moments of di...
AbstractThe study is concerned with second-order and fourth-order moments of jointly distributed ran...
AbstractA large part of statistics is devoted to the estimation of models from the sample covariance...
AbstractThree results are given involving a normally distributed matrix X, namely (1) the expectatio...
Motivated by recent results in random matrix theory we will study the distributions arising from pro...
AbstractFor a left elliptically contoured n × p random matrix Y LECn × p(μ, K, φ), the mth order mom...
In this paper, we consider the matrix which transforms a Kronecker product of vectors into the avera...
AbstractIn this paper, we consider the matrix which transforms a Kronecker product of vectors into t...
This article derives means, variance--covariance matrices of concomitant vectors corresponding to no...
denotes a Kronecker product. From this, second and third moments of quadratic forms are obtained. Th...
In this paper, we consider the matrix which transforms a Kronecker product of vectors into the avera...
This article provides a comprehensive, rigorous, and self-contained introduction to the analysis of ...
AbstractD. Foata and D. Zeilberger (1988, SIAM J. Discrete Math.4, 425–433) and D. Vere-Jones (1988,...
AbstractIn this paper, the authors derived exact expressions for the joint marginal densities of any...
The number of fourth-order moments which can be obtained from a random vector rapidly increases with...
We provide an identity that relates the moment of a product of random variables to the moments of di...