9 citations · 9 across the 3 of their papers we have counts for
6 papers
Bayesian fusion forests for heterogeneous treatment effects on survival from randomised and real-world data
Tijn Jacobs, Stéphanie L. van der Pas, Wessel N. van Wieringen
We develop the Bayesian fusion forest, a nonparametric framework to estimate heterogeneous treatment effects on survival outcomes by combining a randomised controlled trial and rea…
Horseshoe Forests for High-Dimensional Causal Survival Analysis
Tijn Jacobs, Wessel N. van Wieringen, Stéphanie L. van der Pas
We develop a Bayesian tree ensemble model to estimate heterogeneous treatment effects in censored survival data with high-dimensional covariates. Instead of imposing sparsity throu…
rags2ridges: A One-Stop-Shop for Graphical Modeling of High-Dimensional Precision Matrices
Carel F. W. Peeters, Anders Ellern Bilgrau, Wessel N. van Wieringen
A graphical model is an undirected network representing the conditional independence properties between random variables. Graphical modeling has become part and parcel of systems o…
The Spectral Condition Number Plot for Regularization Parameter Determination
Carel F. W. Peeters, Mark A. van de Wiel, Wessel N. van Wieringen
Many modern statistical applications ask for the estimation of a covariance (or precision) matrix in settings where the number of variables is larger than the number of observation…
Gene network reconstruction using global-local shrinkage priors
Gwenaël G. R. Leday, Mathisca C. M. de Gunst, Gino B. Kpogbezan +3
Reconstructing a gene network from high-throughput molecular data is often a challenging task, as the number of parameters to estimate easily is much larger than the sample size. A…
Targeted Fused Ridge Estimation of Inverse Covariance Matrices from Multiple High-Dimensional Data Classes
Anders Ellern Bilgrau, Carel F. W. Peeters, Poul Svante Eriksen +2
We consider the problem of jointly estimating multiple inverse covariance matrices from high-dimensional data consisting of distinct classes. An -penalized maximum likeliho…