Reinhard Furrer | DeepAI

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Featured Co-authors

François Bachoc
42 publications
Emilio Porcu
18 publications
Thierry Klein
13 publications
Fabio Sigrist
9 publications
Moreno Bevilacqua
7 publications
Tarik Faouzi
5 publications
Garyfallos Konstantinoudis
5 publications
Gilles Kratzer
5 publications
Florian Gerber
4 publications
Roman Flury
4 publications
Jakob A. Dambon
3 publications

∙ 06/12/2023

Compatibility of Space-Time Kernels with Full, Dynamical, or Compact Support

We deal with the comparison of space-time covariance kernels having, eit...

0 Tarik Faouzi, et al. ∙

∙ 03/07/2022

Dominant-feature identification in data from Gaussian processes applied to Finnish forest inventory records

In spatial data, location-dependent variation leads to connected structu...

0 Roman Flury, et al. ∙

∙ 12/23/2021

Consistency and asymptotic normality of covariance parameter estimators based on covariance approximations

For a zero-mean Gaussian random field with a parametric covariance funct...

0 Michael Hediger, et al. ∙

∙ 06/19/2021

Discussion on Competition for Spatial Statistics for Large Datasets

We discuss the experiences and results of the AppStatUZH team's particip...

0 Roman Flury, et al. ∙

∙ 06/04/2021

varycoef: An R Package for Gaussian Process-based Spatially Varying Coefficient Models

Gaussian processes (GPs) are well-known tools for modeling dependent dat...

0 Jakob A. Dambon, et al. ∙

∙ 01/06/2021

Joint Variable Selection of both Fixed and Random Effects for Gaussian Process-based Spatially Varying Coefficient Models

Spatially varying coefficient (SVC) models are a type of regression mode...

0 Jakob A. Dambon, et al. ∙

∙ 10/01/2020

Bayesian spatial modelling of terrestrial radiation in Switzerland

The geographic variation of terrestrial radiation can be exploited in ep...

0 Christophe L. Folly, et al. ∙

∙ 07/29/2020

Asymptotically Equivalent Prediction in Multivariate Geostatistics

Cokriging is the common method of spatial interpolation (best linear unb...

0 François Bachoc, et al. ∙

∙ 06/12/2020

Identification of Dominant Features in Spatial Data

Dominant features of spatial data are structures or patterns that become...

0 Roman Flury, et al. ∙

∙ 05/29/2020

Multiresolution Decomposition of Areal Count Data

Multiresolution decomposition is commonly understood as a procedure to c...

0 Roman Flury, et al. ∙

∙ 01/22/2020

Maximum Likelihood Estimation of Spatially Varying Coefficient Models for Large Data with an Application to Real Estate Price Prediction

In regression models for spatial data, it is often assumed that the marg...

0 Jakob A. Dambon, et al. ∙

∙ 11/25/2019

Asymptotic properties of the maximum likelihood and cross validation estimators for transformed Gaussian processes

The asymptotic analysis of covariance parameter estimation of Gaussian p...

0 François Bachoc, et al. ∙

∙ 11/20/2019

Additive Bayesian Network Modelling with the R Package abn

The R package abn is designed to fit additive Bayesian models to observa...

0 Gilles Kratzer, et al. ∙

∙ 06/02/2019

Combining Heterogeneous Spatial Datasets with Process-based Spatial Fusion Models: A Unifying Framework

In modern spatial statistics, the structure of data that is collected ha...

0 Craig Wang, et al. ∙

∙ 02/18/2019

Is a single unique Bayesian network enough to accurately represent your data?

Bayesian network (BN) modelling is extensively used in systems epidemiol...

0 Gilles Kratzer, et al. ∙

∙ 09/18/2018

Comparison between Suitable Priors for Additive Bayesian Networks

Additive Bayesian networks are types of graphical models that extend the...

0 Gilles Kratzer, et al. ∙

∙ 08/03/2018

Information-Theoretic Scoring Rules to Learn Additive Bayesian Network Applied to Epidemiology

Bayesian network modelling is a well adapted approach to study messy and...

0 Gilles Kratzer, et al. ∙

∙ 04/30/2018

eggCounts: a Bayesian hierarchical toolkit to model faecal egg count reductions

This is a vignette for the R package eggCounts version 2.0. The package ...

0 Craig Wang, et al. ∙

∙ 04/30/2018

optimParallel: an R Package Providing Parallel Versions of the Gradient-Based Optimization Methods of optim()

The R package optimParallel provides a parallel version of the gradient-...

0 Florian Gerber, et al. ∙

∙ 04/19/2018

varrank: an R package for variable ranking based on mutual information with applications to observed systemic datasets

This article describes the R package varrank. It has a flexible implemen...

4 Gilles Kratzer, et al. ∙

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