Marius Hofert

According to our database, Marius Hofert authored at least 28 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Comparison of correlation-based measures of concordance in terms of asymptotic variance.

Takaaki Koike, Marius Hofert

J. Multivar. Anal., 2024

Policy Optimization by Looking Ahead for Model-based Offline Reinforcement Learning.

Yang Liu, Marius Hofert

Proceedings of the IEEE International Conference on Robotics and Automation, 2024

Implicit and Explicit Policy Constraints for Offline Reinforcement Learning.

Yang Liu, Marius Hofert

Proceedings of the Causal Learning and Reasoning, 2024

2023

Dependence Model Assessment and Selection with DecoupleNets.

Marius Hofert, Avinash Prasad, Mu Zhu

J. Comput. Graph. Stat., 2023

2022

Multivariate Normal Variance Mixtures in <i>R</i>: The <i>R</i> Package nvmix.

Erik Hintz, Marius Hofert, Christiane Lemieux

J. Stat. Softw., 2022

2021

Quasi-Random Sampling for Multivariate Distributions via Generative Neural Networks.

Marius Hofert, Avinash Prasad, Mu Zhu

J. Comput. Graph. Stat., 2021

Normal variance mixtures: Distribution, density and parameter estimation.

Erik Hintz, Marius Hofert, Christiane Lemieux

Comput. Stat. Data Anal., 2021

Outer power transformations of hierarchical Archimedean copulas: Construction, sampling and estimation.

Jan Górecki, Marius Hofert, Ostap Okhrin

Comput. Stat. Data Anal., 2021

RafterNet: Probabilistic predictions in multi-response regression.

Marius Hofert, Avinash Prasad, Mu Zhu

CoRR, 2021

2020

Zigzag Expanded Navigation Plots in R: The R Package zenplots.

Marius Hofert, Wayne Oldford

J. Stat. Softw., 2020

Random number generators produce ties: Why and how many.

Marius Hofert

CoRR, 2020

Multivariate time-series modeling with generative neural networks.

Marius Hofert, Avinash Prasad, Mu Zhu

CoRR, 2020

Applications of Multivariate Quasi-Random Sampling with Neural Networks.

Marius Hofert, Avinash Prasad, Mu Zhu

Proceedings of the Monte Carlo and Quasi-Monte Carlo Methods, 2020

2019

A framework for measuring association of random vectors via collapsed random variables.

Marius Hofert, Wayne Oldford, Avinash Prasad, Mu Zhu

J. Multivar. Anal., 2019

2018

Hierarchical Archimax copulas.

Marius Hofert, Raphaël Huser, Avinash Prasad

J. Multivar. Anal., 2018

Quasi-random number generators for multivariate distributions based on generative neural networks.

Marius Hofert, Avinash Prasad, Mu Zhu

CoRR, 2018

2017

Quasi-random numbers for copula models.

Mathieu Cambou, Marius Hofert, Christiane Lemieux

Stat. Comput., 2017

2016

An approach to structure determination and estimation of hierarchical Archimedean Copulas and its application to Bayesian classification.

Jan Górecki, Marius Hofert, Martin Holena

J. Intell. Inf. Syst., 2016

2015

Construction and sampling of Archimedean and nested Archimedean Lévy copulas.

Oliver Grothe, Marius Hofert

J. Multivar. Anal., 2015

2013

On Sampling from the Multivariate t Distribution.

Marius Hofert

R J., 2013

A note on generalized inverses.

Paul Embrechts, Marius Hofert

Math. Methods Oper. Res., 2013

Sibuya copulas.

Marius Hofert, Frédéric Vrins

J. Multivar. Anal., 2013

Densities of nested Archimedean copulas.

Marius Hofert, David Pham

J. Multivar. Anal., 2013

2012

Likelihood inference for Archimedean copulas in high dimensions under known margins.

Marius Hofert, Martin Mächler, Alexander J. McNeil

J. Multivar. Anal., 2012

2011

Sampling Exponentially Tilted Stable Distributions.

Marius Hofert

ACM Trans. Model. Comput. Simul., 2011

Efficiently sampling nested Archimedean copulas.

Marius Hofert

Comput. Stat. Data Anal., 2011

2010

Constructing hierarchical Archimedean copulas with Lévy subordinators.

Christian Hering, Marius Hofert, Jan-Frederik Mai, Matthias Scherer

J. Multivar. Anal., 2010

2008

Sampling Archimedean copulas.

Marius Hofert

Comput. Stat. Data Anal., 2008