We consider normal [reverse not equivalent] Gaussian seemingly unrelated regressions (SUR) with incomplete data (ID). Imposing a natural minimal set of conditional independence constraints, we find a restricted SUR/ID model whose likelihood function and parameter space factor into the product of...

A multivariate normal statistical model defined by the Markov properties determined by an acyclic digraph admits a recursive factorization of its likelihood function (LF) into the product of conditional LFs, each factor having the form of a classical multivariate linear regression model...

In this paper, we define general canonical correlations, which generalize the canonical correlations developed by Hotelling, and general canonical covariate pairs, the corresponding linear statistic. We also define canonical variance distances with corresponding canonical distance variates. In a...

Statistical inference for the parameters of a multivariate normal distribution Np([mu], [Sigma]) based on a sample with missing observations is straightforward when the missing data pattern is monotone (= nested), reducing to the analysis of several normal linear regression models by step-wise...

The first problem considered is that of testing for the reality of the covariance matrix of a p-dimensional complex normal distribution, while the second is that of testing that a 2p-dimensional real normal distribution has a p-dimensional complex structure. Both problems are reduced by...

In an effort to assess the latest thinking in the Roman Catholic Church on economic matters, we examine the newest encyclical by Pope Benedict XVI, Caritas in Veritate (Charity in Truth) for guidance concerning marketing and business strategy. Core ethical values, consistent with historical...

It is shown that the information matrices of maximal parameter subsystems in linear models are linear functions of the moment matrices. With this result, design problems for maximal parameter subsystems are shown to be equivalent to design problems for the full parameter vector of a minimally...