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Fotografi av Dietrich von Rosen

Dietrich von Rosen

Gästprofessor i matematisk statistik

Jag är gästprofessor i matematisk statistik vid Matematiska institutionen, Linköpings universitet, och professor i statistik vid Institutionen för energi och teknik, Sveriges lantbruksuniversitet.

Forskningsprofil

(In English) The year 1998 von Rosen got a full professorship in Statistics at the Swedish University of Agricultural Sciences (SLU) and 2009-2024 he was also working as adjoint professor in Mathematical Statistics at Linköping University. In year 2024 he formally retired from SLU but is still connected with MAI at Linköping University. Moreover, von Rosen has been working at the medical university in Stockholm, the Karolinska Institute, for more than six years.

von Rosen’s research profile comprises linear models, multivariate analysis, bilinear models, high-dimensional analysis and matrix algebra. More than 130 peer reviewed articles have been written and 19 Ph.D. students have under supervision by von Rosen successfully defended their thesis.

von Rosen have two published books entitled “Advanced Multivariate Statistics with Matrices” and “Bilinear Regression Analysis, an Introduction”. He is Editor- in- Chief of Journal of Multivariate Analysis. von Rosen has organized several international conferences and workshops. In 2014 von Rosen became Honorary Doctor of Tartu University, Estonia. He has many ongoing international collaborations.

I samarbete med

Forskning

Doktorander

Tidigare doktorander

  • Joseph Nzabanita (dokt.). Avhandlingens titel:
  • Jolanta Pielaszkiewicz (dokt.). Avhandlingens titel: 
  • Innocent Ngaruye (dokt.). Avhandlingens titel: 

Publikationer

2025

Daniel Klein, Anuradha Roy, Dietrich von Rosen, Katarzyna Filipiak (2025) SANKHYA-SERIES B-APPLIED AND INTERDISCIPLINARY STATISTICS (Artikel i tidskrift)

2024

Dietrich von Rosen, Martin Singull (2024) Annals of the Institute of Statistical Mathematics, Vol. 76, s. 511-534 (Artikel i tidskrift)
Katarzyna Filipiak, Dietrich von Rosen, Martin Singull, Wojciech Rejchel (2024)
Anna Szczepanska-Alvarez, Adolfo Alvarez, Artur Szwengiel, Dietrich von Rosen (2024) Journal of Agricultural Biological and Environmental Statistics, Vol. 29, s. 257-276 (Artikel i tidskrift)
Shuangzhe Liu, Götz Trenkler, Tonu Kollo, Dietrich von Rosen, Oskar Maria Baksalary (2024) Statistical papers, Vol. 65, s. 2605-2639 (Artikel i tidskrift)
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2024) Communications in Statistics - Theory and Methods, Vol. 53, s. 1122-1134 (Artikel i tidskrift)

2023

Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2023) Trends in Mathematical, Information and Data Sciences: A Tribute to Leandro Pardo, s. 287-305 (Kapitel i bok, del av antologi)
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2023)
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2023)

2022

Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2022) Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains, s. 119-135 (Kapitel i bok, del av antologi)
Felix Wamano, Leonard Atuhaire, Innocent Ngaruye, Dietrich von Rosen, Martin Singull (2022)
Dietrich von Rosen, Martin Singull (2022)
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2022)
Emelyne Umunoza Gasana, Dietrich von Rosen, Martin Singull (2022)
Béatrice Byukusenge, Dietrich von Rosen, Martin Singull (2022) Journal of Statistical Theory and Practice, Vol. 16 (Artikel i tidskrift)

Böcker

Recent Developments in Multivariate and Random Matrix Analysis

Omslaget till boken
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.

Organisation