Klüppelberg, Claudia; Pham, Viet Son
Estimation of causal continuous‐time autoregressive moving average random fields
Scandinavian Journal of Statistics
2020
48
1
Jan
132-163

Drton, Mathias; Han, Fang; Shi, Hongjian
High-dimensional consistent independence testing with maxima of rank correlations
Annals of Statistics
2020
48
6
Dec
3206-3227

Lin, Lina; Drton, Mathias; Shojaie, Ali
Statistical Significance in High-dimensional Linear Mixed Models
171-181
Proceedings of the 2020 ACM-IMS on Foundations of Data Science Conference
Association for Computing Machinery
2020

Kley, Oliver; Klüppelberg, Claudia; Paterlini, Sandra
Modelling extremal dependence for operational risk by a bipartite graph
Journal of Banking & Finance
2020
117
Aug
105855

Drton, Mathias; Robeva, Elina; Weihs, Luca
Nested covariance determinants and restricted trek separation in Gaussian graphical models
Bernoulli
2020
26
4
Aug
2503-2540

Jin, Kelly;Wilson, Kenneth A.;Beck, Jennifer N.;Nelson, Christopher S.;Brownridge, George W.;Harrison, Benjamin R.;Djukovic, Danijel;Raftery, Daniel;Brem, Rachel B.;Yu, Shiqing;Drton, Mathias;Shojaie, Ali;Kapahi, Pankaj;Promislow, Daniel
Genetic and metabolomic architecture of variation in diet restriction-mediated lifespan extension in Drosophila
PLOS Genetics
2020
16
7
Jul
e1008835

Bachner, Joachim;Sturm, David J.;Haug, Stephan;Demetriou, Yolanda
Multi-level validation of the German physical activity self-efficacy scale in a sample of female sixth-graders
BMC Public Health
2020
20
1

Sturm, David J.;Bachner, Joachim;Haug, Stephan;Demetriou, Yolanda
The German Basic Psychological Needs Satisfaction in Physical Education Scale: Adaption and Multilevel Validation in a Sample of Sixth-Grade Girls
International Journal of Environmental Research and Public Health
2020
17
5
1554

Behme, A.; Klüppelberg, C.; Reinert, G.
Ruin probabilities for risk processes in a bipartite network
Stochastic Models
2020
36
4
May
548-573

Wang, Y Samuel;Drton, Mathias
High-dimensional causal discovery under non-Gaussianity
Biometrika
2020
107
1
Mar
41–59