32 citations · 67 across the 29 of their papers we have counts for
8 papers · 1 filter
Single-Index Importance Sampling with Stratification
Erik Hintz, Marius Hofert, Christiane Lemieux +1
In many stochastic problems, the output of interest depends on an input random vector mainly through a single random variable (or index) via an appropriate univariate transformatio…
Smooth bootstrapping of copula functionals
Maximilian Coblenz, Oliver Grothe, Klaus Herrmann +1
The smooth bootstrap for estimating copula functionals in small samples is investigated. It can be used both to gauge the distribution of the estimator in question and to augment t…
Random number generators produce collisions: Why, how many and more
Marius Hofert
It seems surprising that when applying widely used random number generators to generate one million random numbers on modern architectures, one obtains, on average, about 116 colli…
Normal variance mixtures: Distribution, density and parameter estimation
Erik Hintz, Marius Hofert, Christiane Lemieux
Normal variance mixtures are a class of multivariate distributions that generalize the multivariate normal by randomizing (or mixing) the covariance matrix via multiplication by a…
Quasi-random numbers for copula models
Mathieu Cambou, Marius Hofert, Christiane Lemieux
The present work addresses the question how sampling algorithms for commonly applied copula models can be adapted to account for quasi-random numbers. Besides sampling methods such…
An importance sampling approach for copula models in insurance
Philipp Arbenz, Mathieu Cambou, Marius Hofert
An importance sampling approach for sampling copula models is introduced. We propose two algorithms that improve Monte Carlo estimators when the functional of interest depends main…
Parallel and other simulations in R made easy: An end-to-end study
Marius Hofert, Martin Mächler
It is shown how to set up, conduct, and analyze large simulation studies with the new R package simsalapar = simulations simplified and launched parallel. A simulation study typica…
Estimators for Archimedean copulas in high dimensions
Marius Hofert, Martin Maechler, Alexander J. McNeil
The performance of known and new parametric estimators for Archimedean copulas is investigated, with special focus on large dimensions and numerical difficulties. In particular, me…