Recent Developments in Multivariate and Random Matrix Analysis

Zusatztext

<p>This volume is a tribute to Professor Dietrich von Rosen on the occasion of his 65<sup>th</sup> birthday. It contains a collection of twenty original papers. The contents of the papers evolve around multivariate analysis and random matrices with topics such as high-dimensional analysis, goodness-of-fit measures, variable selection and information criteria, inference of covariance structures, the Wishart distribution and growth curve models. </p><div></div>

Autorenportrait

<p><b>Thomas Holgersson </b>is Professor of statistics at Linnaeus. He is currently a review panel member of the Swedish research council board and involved in the development of a nationwide graduate school in statistics. He has been working in multiple fields such as econometrics and time series analysis but is now primarily working with random matrix analysis. He is associate editor of Journal of Multivariate Analysis.</p> <p><b>Martin Singull</b> is Associate Professor in Mathematical Statistic and Head of Division of Mathematical Statistics at the Department of Mathematics, Linköping University. He is also Assistant Director for the Research School in Interdisciplinary Mathematics at Linköping University. Dr Singulls research focuses on supervised learning for Gaussian linear and bilinear (also known as Growth Curve) models with special focus on inference for covariance matrices with various structures.<b></b></p> <p></p>

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