Photo of Dietrich von Rosen

Dietrich von Rosen

Visiting Professor

Visiting professor in Mathematical Statistics

I am visiting professor in Mathematical Statistics at Linköping University at the Department of Mathematics, and professor in Statistics at the Swedish University of Agricultural Sciences at the Department of Energy and Technology.

Reserach profile

My research profile comprises linear models, multivariate analysis, bilinear models, high-dimensional analysis and matrix algebra. More than 100 peer reviewed articles have been written and 16 Ph.D. students have successfully defended their thesis. Three of these theses have been awarded the best thesis of the year in Mathematical Statistics/Statistics in Sweden. I have published one book entitled “Advanced Multivariate Statistics with Matrices” and a new book “Bilinear Regression Analysis, an Introduction” is to be published next year.

My work at Linköping University

I have mostly been working with Martin Singull but recently also started to work with Xiangfeng Yang. Over the years we have jointly organized three international meetings (funded by the Swedish Research Council and the Nordic Councils of Ministers) and jointly organized sessions within larger international conferences. Three Ph.D. students have defended their thesis and one more is on the way. Fifteen peer-reviewed articles have been produced together with Martin Singull and sometimes other coauthors. A number of successful applications have also been written.

In collaboration with

Professional activities

Professional activities

  • Leader of a research group in Biometry at the Swedish University of Agricultural Sciences
  • Associate editor of Acta et Commentationes Universitatis Tartuensis de Mathematica
  • Associate editor of Discussiones Mathematicae, Probability and Statistics
  • Associate editor of Journal of Multivariate Analysis
  • Associate editor of Statistical Papers
  • Swedish representative, International Biometric Society - Nordic-Baltic Region


Honorary Doctor, Tartu University, Estonia



Organizer of international meetings

  • Head of the international program committee of LinStat2014, 2014, Linköping, Sweden
  • Head of the  program committee  of the 10th Tartu Conference on Multivariate Statistics, 2016
  • Member of the international scientific committee of Linstat2016, 2016, Istanbul
  • Member of the international scientific committee of The First East African Conference on Mathematical Statistics with Applications, Kigali, Rwanda, 2017
  • Session organizer at LINSTAT2016 conference. Istanbul, 2016
  • Session organizer “Mixed linear models with applications to small area estimation” at CFE-CMStatistics, London, 16-18 December, 2017

External project funding

The Swedish Foundation for Humanities and Social Sciences


National Ph.D. course in Statistical Inference for Statistics students in Sweden



PhD students

Former PhD students



Dietrich von Rosen, Martin Singull (2024) Using the growth curve model in classification of repeated measurements Annals of the Institute of Statistical Mathematics Continue to DOI
Katarzyna Filipiak, Dietrich von Rosen, Martin Singull, Wojciech Rejchel (2024) Estimation under inequality constraints in univariate and multivariate linear models


Anna Szczepanska-Alvarez, Adolfo Alvarez, Artur Szwengiel, Dietrich von Rosen (2023) Testing Correlation in a Three-Level Model Journal of Agricultural Biological and Environmental Statistics Continue to DOI
Shuangzhe Liu, Gotz Trenkler, Tonu Kollo, Dietrich von Rosen, Oskar Maria Baksalary (2023) Professor Heinz Neudecker and matrix differential calculus Statistical papers Continue to DOI
Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2023) On Residual Analysis in the GMANOVA-MANOVA Model Trends in Mathematical, Information and Data Sciences: A Tribute to Leandro Pardo, p. 287-305 Continue to DOI
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2023) Moments of the Likelihood-based Classification Function using Growth Curves
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2023) Edgeworth-type expansion of the density of the classifier when growth curves are classified via likelihood


Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2022) On the Identification of Extreme Elements in a Residual for the GMANOVA-MANOVA Model Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains, p. 119-135 Continue to DOI
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2022) Moments of the likelihood-based discriminant function Communications in Statistics - Theory and Methods Continue to DOI
Felix Wamano, Leonard Atuhaire, Innocent Ngaruye, Dietrich von Rosen, Martin Singull (2022) Estimation of trends in household living standards in Uganda using a GMANOVA-MANOVA model with rank restrictions
Dietrich von Rosen, Martin Singull (2022) Classification of repeated measurements using growth curves
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2022) Approximated misclassification errors for the likelihood based discriminant function via Edgetworth-type expansion
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2022) The first two cumulants of the (quadratic) likelihood-based discriminant functions
Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2022) On an Important Residual in the GMANOVA-MANOVA Model Journal of Statistical Theory and Practice, Vol. 16 Continue to DOI
Shinpei Imori, Dietrich von Rosen, Ryoya Oda (2022) Growth Curve Model with Bilinear Random Coefficients SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY, Vol. 84, p. 477-508 Continue to DOI


Recent Developments in Multivariate and Random Matrix Analysis

The cover of
Festschrift in Honour of Dietrich von Rosen
Edited by Thomas Holgersson and Martin Singull

This volume is a tribute to Professor Dietrich von Rosen on the occasion of his 65th 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.

More about the book