132 citations · 343 across the 32 of their papers we have counts for
6 papers · 1 filter
varycoef: An R Package for Gaussian Process-based Spatially Varying Coefficient Models
Jakob A. Dambon, Fabio Sigrist, Reinhard Furrer
Gaussian processes (GPs) are well-known tools for modeling dependent data with applications in spatial statistics, time series analysis, or econometrics. In this article, we presen…
Is a single unique Bayesian network enough to accurately represent your data?
Gilles Kratzer, Reinhard Furrer
Bayesian network (BN) modelling is extensively used in systems epidemiology. Usually it consists in selecting and reporting the best-fitting structure conditional to the data. A ma…
optimParallel: an R Package Providing Parallel Versions of the Gradient-Based Optimization Methods of optim()
Florian Gerber, Reinhard Furrer
The R package optimParallel provides a parallel version of the gradient-based optimization methods of optim(). The main function of the package is optimParallel(), which has the sa…
EggCounts: a Bayesian hierarchical toolkit to model faecal egg count reductions
Craig Wang, Reinhard Furrer
This is a vignette for the R package eggCounts version 2.0. The package implements a suite of Bayesian hierarchical models dealing with faecal egg count reductions. The models are…
dotCall64: An Efficient Interface to Compiled C/C++ and Fortran Code Supporting Long Vectors
Florian Gerber, Kaspar Mösinger, Reinhard Furrer
The R functions .C() and .Fortran() can be used to call compiled C/C++ and Fortran code from R. This so-called foreign function interface is convenient, since it does not require a…
Valid parameter space of a bivariate Gaussian Markov random field with a generalized block-Toeplitz precision matrix
Mattia Molinaro, Reinhard Furrer
Gaussian Markov random fields (GMRFs) are extensively used in statistics to model area-based data and usually depend on several parameters in order to capture complex spatial corre…