This paper derives some optimum transmit and receive antenna coefficients in wireless multipath channels based on the spherical vector wave multimode expansion of the multiple-input multiple-output (MIMO) channel matrix. The derived antenna coefficients satisfy the following specific optimization criteria: (i) maximum MIMO mean effective link gain (link MEG) based on the multimode channel reali...

The NORTA method for multivariate generation is a fast general purpose method for generating samples of a random vector with given marginal distributions and given productmoment or rank correlation matrix. However, this method has been shown to fail to work for some feasible correlation matrices. (A matrix is feasible if there exists a random vector with the given marginal distributions and the...

Many parameters and positive-definiteness are two major obstacles in estimating and modelling a correlation matrix for longitudinal data. In addition, when longitudinal data is incomplete, incorrectly modelling the correlation matrix often results in bias in estimating mean regression parameters. In this paper, we introduce a flexible and parsimonious class of regression models for a covariance...

In this paper, we describe an unsupervised measure for quantifying the ‘informativeness’ of correlation matrices formed from the pairwise similarities or relationships among data instances. The measure quantifies the heterogeneity of the correlations and is defined as the distance between a correlation matrix and the nearest correlation matrix with constant off-diagonal entries. This non-parame...

For a large class of quantum systems, the statistical properties of their spectrum show remarkable agreement with random matrix predictions. Recent advances show that the scope of random matrix theory is much wider. In this work, we show that the random matrix approach can be beneficially applied to a completely different classical domain, namely, to the empirical correlation matrices obtained ...

In some cases, the matrix available to the analyst/decision-maker is complete, but it is an invalid (not positive semi-definite) correlation matrix. There could be many reasons that give rise to such invalid matrices (Mishra, 2004). In such cases, the problem is to obtain a positive semi-definite approximate correlation matrix, which, in some sense, is closest to the given invalid matrix. A num...

The NORmal-To-Anything (NORTA) algorithm requires a correlation matrix of multivariate normal variables to convert a multivariate normal vector to any other distribution. This paper presents a new simulation method that works in combination with the NORTA algorithm yet avoids having to solve some complicated equations which need to be solved to achieve this matrix. The performance of the propos...

This study investigates whether, how, and why the matrix of correlations across international equity markets changes over time. A theoretical model is proposed to specify potential economic determinants of this correlation structure. The empirical validity of this economic model is investigated by employing daily returns for different national stock indexes, from 1972 through 1993, to construct...