Suppose that n independent observations are drawn from a multivariate normal distribution Np([mu],[Sigma]) with both mean vector [mu] and covariance matrix [Sigma] unknown. We consider the problem of estimating the precision matrix [Sigma]-1 under the squared loss . It is well known that the...

In this research, we propose a new methodology to assess structural similarity of air navigation route systems in 58 countries. We identify functional dependencies among network metrics through regression analysis. We build a graph for the network metrics, with each metric as a node and a link...

In this paper, we study the problem of estimating the covariance matrix [Sigma] and the precision matrix [Omega] (the inverse of the covariance matrix) in a star-shape model with missing data. By considering a type of Cholesky decomposition of the precision matrix [Omega]=[Psi]'[Psi], where...

We study the problems of hypothesis testing and point estimation for the correlation coefficient between the disturbances in the system of two seemingly unrelated regression equations. An objective Bayesian solution to each problem is proposed based on combined use of the invariant loss function...

This paper presents a Bayesian spatial method for analysing the site index data from the Missouri Ozark Forest Ecosystem Project (MOFEP). Based on ecological background and availability, we select three variables, the aspect class, the soil depth and the land type association as covariates for...