Mark A. van de Wiel

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All published works

Action	Title	Year	Authors
+ PDF Chat	Fusion of Tree-induced Regressions for Clinico-genomic Data	2024	Jeroen M. Goedhart Mark A. van de Wiel Wessel N. van Wieringen Thomas Klausch
+ PDF Chat	Refining CART Models for Covariate Shift with Importance Weight	2024	Mingyang Cai Thomas Klausch Mark A. van de Wiel
+ PDF Chat	A flexible model for Record Linkage	2024	Kayané Robach Stéphanie van der Pas Mark A. van de Wiel Michel H. Hof
+ PDF Chat	Guiding adaptive shrinkage by co-data to improve regression-based prediction and feature selection	2024	Mark A. van de Wiel Wessel N. van Wieringen
+	Linked shrinkage to improve estimation of interaction effects in regression models	2024	Mark A. van de Wiel Matteo Amestoy Jeroen Hoogland
+ PDF Chat	Penalized regression with multiple sources of prior effects	2023	Armin Rauschenberger Zied Landoulsi Mark A. van de Wiel Enrico Glaab
+ PDF Chat	A Bayesian accelerated failure time model for interval censored three-state screening outcomes	2023	Thomas Klausch Eddymurphy U. Akwiwu Mark A. van de Wiel Veerle M.H. Coupé Johannes Berkhof
+ PDF Chat	ecpc: an R-package for generic co-data models for high-dimensional prediction	2023	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel
+	Think before you shrink: Alternatives to default shrinkage methods can improve prediction accuracy, calibration and coverage	2023	Mark A. van de Wiel Gwenaël G. R. Leday Jeroen Hoogland Martijn W. Heymans Erik W. van Zwet A. H. Zwinderman
+	Linked shrinkage to improve estimation of interaction effects in regression models	2023	Mark A. van de Wiel Matteo Amestoy Jeroen Hoogland
+	Co-data Learning for Bayesian Additive Regression Trees	2023	Jeroen M. Goedhart Thomas Klausch Jurriaan Janssen Mark A. van de Wiel
+	Fast Marginal Likelihood Estimation of Penalties for Group-Adaptive Elastic Net	2022	Mirrelijn M. van Nee Tim van de Brug Mark A. van de Wiel
+	Estimation of predictive performance in high-dimensional data settings using learning curves	2022	Jeroen M. Goedhart Thomas Klausch Mark A. van de Wiel
+ PDF Chat	Semi‐supervised empirical Bayes group‐regularized factor regression	2022	Magnus Münch Mark A. van de Wiel Aad van der Vaart Carel F.W. Peeters
+	ecpc: An R-package for generic co-data models for high-dimensional prediction	2022	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel
+	Estimation of Predictive Performance in High-Dimensional Data Settings using Learning Curves	2022	Jeroen M. Goedhart Thomas Klausch Mark A. van de Wiel
+	Penalised regression with multiple sources of prior effects	2022	Armin Rauschenberger Zied Landoulsi Mark A. van de Wiel Enrico Glaab
+ PDF Chat	Flexible co‐data learning for high‐dimensional prediction	2021	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel
+ PDF Chat	Fast Cross-validation for Multi-penalty High-dimensional Ridge Regression	2021	Mark A. van de Wiel Mirrelijn M. van Nee Armin Rauschenberger
+	Conditional Inference Procedures in a Permutation Test Framework [R package coin version 1.4-0]	2021	Torsten Hothorn Henric Winell Kurt Hornik Mark A. van de Wiel Achim Zeileis
+	A Bayesian accelerated failure time model for interval censored three-state screening outcomes	2021	Thomas Klausch Eddymurphy U. Akwiwu Mark A. van de Wiel Veerle M.H. Coupé Johannes Berkhof
+	Semi-supervised empirical Bayes group-regularized factor regression	2021	Magnus Münch Mark A. van de Wiel Aad van der Vaart Carel F.W. Peeters
+	Fast marginal likelihood estimation of penalties for group-adaptive elastic net	2021	Mirrelijn M. van Nee Tim van de Brug Mark A. van de Wiel
+ PDF Chat	Drug sensitivity prediction with normal inverse Gaussian shrinkage informed by external data	2020	Magnus Münch Mark A. van de Wiel Sylvia Richardson Gwenaël G. R. Leday
+	Flexible co-data learning for high-dimensional prediction	2020	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel
+	Updating of the Gaussian graphical model through targeted penalized estimation	2020	Wessel N. van Wieringen Koen A. Stam Carel F.W. Peeters Mark A. van de Wiel
+	Fast cross-validation for multi-penalty ridge regression	2020	Mark A. van de Wiel Mirrelijn M. van Nee Armin Rauschenberger
+	Flexible co-data learning for high-dimensional prediction	2020	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel
+	Adaptive group-regularized logistic elastic net regression	2019	Magnus Münch Carel F.W. Peeters Aad van der Vaart Mark A. van de Wiel
+ PDF Chat	Sparse classification with paired covariates	2019	Armin Rauschenberger Iuliana Ciocănea‐Teodorescu Marianne A. Jonker Renée X. de Menezes Mark A. van de Wiel
+	Conditional Inference Procedures in a Permutation Test Framework [R package coin version 1.3-1]	2019	Torsten Hothorn Henric Winell Kurt Hornik Mark A. van de Wiel Achim Zeileis
+ PDF Chat	Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models	2019	Jurre R. Veerman Gwenaël G. R. Leday Mark A. van de Wiel
+ PDF Chat	The spectral condition number plot for regularization parameter evaluation	2019	Carel F.W. Peeters Mark A. van de Wiel Wessel N. van Wieringen
+	Stable prediction with radiomics data.	2019	Carel F.W. Peeters Caroline Übelhör Steven W. Mes Roland M. Martens Thomas Koopman Pim de Graaf Floris H. P. van Velden Ronald Boellaard Jonas A. Castelijns Dennis E. te Beest
+	Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models	2019	Jurre R. Veerman Gwenaël G. R. Leday Mark A. van de Wiel
+	Incorporating prior information and borrowing information in high-dimensional sparse regression using the horseshoe and variational Bayes	2019	Gino B. Kpogbezan Mark A. van de Wiel Wessel N. van Wieringen Aad van der Vaart
+	Stable prediction with radiomics data	2019	Carel F.W. Peeters Caroline Übelhör Steven W. Mes Roland M. Martens Thomas Koopman Pim de Graaf Floris H. P. van Velden Ronald Boellaard Jonas A. Castelijns Dennis E. te Beest
+	Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models	2019	Jurre R. Veerman Gwenael G. R. Leday Mark A. van de Wiel
+ PDF Chat	Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction	2018	Mark A. van de Wiel Dennis E. te Beest Magnus Münch
+	Adaptive group-regularized logistic elastic net regression.	2018	Magnus Münch Carel F.W. Peeters Aad van der Vaart Mark A. van de Wiel
+	Detecting SNPs with interactive effects on a quantitative trait	2018	Armin Rauschenberger Renée X. de Menezes Mark A. van de Wiel Natasja M. van Schoor Marianne A. Jonker
+	Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data	2018	Thomas Klausch Peter van de Ven Tim van de Brug Mark A. van de Wiel Johannes Berkhof
+	Adaptive group-regularized logistic elastic net regression	2018	Magnus Münch Carel F.W. Peeters Aad van der Vaart Mark A. van de Wiel
+ PDF Chat	Improved high-dimensional prediction with Random Forests by the use of co-data	2017	Dennis E. te Beest Steven W. Mes Saskia M. Wilting Ruud H. Brakenhoff Mark A. van de Wiel
+ PDF Chat	Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis	2017	Iris Eekhout Mark A. van de Wiel Martijn W. Heymans
+	Improved high-dimensional prediction with Random Forests by the use of co-data	2017	Dennis E. te Beest Steven W. Mes Ruud H. Brakenhoff Mark A. van de Wiel
+ PDF Chat	An empirical Bayes approach to network recovery using external knowledge	2017	Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Gwenaël G. R. Leday Mark A. van de Wiel
+	Gene network reconstruction using global-local shrinkage priors	2017	Gwenaël G. R. Leday Mathisca C. M. de Gunst Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Mark A. van de Wiel
+	Learning from a lot: Empirical Bayes in high-dimensional prediction settings	2017	Mark A. van de Wiel Dennis E. te Beest Magnus Münch
+	Blood‐based metabolic signatures in Alzheimer's disease	2017	Francisca A. de Leeuw Carel F.W. Peeters Maartje I. Kester Amy C. Harms Eduard A. Struys Thomas Hankemeier Herman van Vlijmen Sven J. van der Lee Cornelia M. van Duijn Philip Scheltens
+	Improved high-dimensional prediction with Random Forests by the use of co-data	2017	Dennis E. te Beest Steven W. Mes Ruud H. Brakenhoff Mark A. van de Wiel
+ PDF Chat	Erratum to: Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation	2016	Simone Wahl Anne‐Laure Boulesteix Astrid Zierer Barbara Thorand Mark A. van de Wiel
+ PDF Chat	Assessment of predictive performance in incomplete data by combining internal validation and multiple imputation	2016	Simone Wahl Anne‐Laure Boulesteix Astrid Zierer Barbara Thorand Mark A. van de Wiel
+	An empirical Bayes approach to network recovery using external knowledge	2016	Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Gwenaël G. R. Leday Mark A. van de Wiel
+	An empirical Bayes approach to network recovery using external knowledge	2016	Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Gwenaël G. R. Leday Mark A. van de Wiel
+	Gene network reconstruction using global-local shrinkage priors	2015	Gwenaël G. R. Leday Mathisca C. M. de Gunst Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Mark A. van de Wiel
+ PDF Chat	Better prediction by use of co‐data: adaptive group‐regularized ridge regression	2015	Mark A. van de Wiel Tonje G. Lien Wina Verlaat Wessel N. van Wieringen Saskia M. Wilting
+	Gene network reconstruction using global-local shrinkage priors	2015	Gwenaël G. R. Leday Mathisca C. M. de Gunst Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Mark A. van de Wiel
+	Better prediction by use of co-data: Adaptive group-regularized ridge regression	2014	Mark A. van de Wiel Tonje G. Lien Wina Verlaat Wessel N. van Wieringen Saskia M. Wilting
+ PDF Chat	ShrinkBayes: a versatile R-package for analysis of count-based sequencing data in complex study designs	2014	Mark A. van de Wiel Maarten Neerincx Tineke E. Buffart Daoud Sie Henk M.W. Verheul
+	Analysis of Next Generation Sequencing Data Using Integrated Nested Laplace Approximation (INLA)	2014	Andrea Riebler Mark D. Robinson Mark A. van de Wiel
+	Better prediction by use of co-data: Adaptive group-regularized ridge regression	2014	Mark A. van de Wiel Tonje G. Lien Wina Verlaat Wessel N. van Wieringen Saskia M. Wilting
+	Modeling association between DNA copy number and gene expression with constrained piecewise linear regression splines	2013	Gwenaël G. R. Leday Aad van der Vaart Wessel N. van Wieringen Mark A. van de Wiel
+	General power and sample size calculations for high-dimensional genomic data	2013	Maarten van Iterson Mark A. van de Wiel Judith M. Boer Renée X. de Menezes
+	Confidence scores for prediction models	2011	Thomas A. Gerds Mark A. van de Wiel
+ PDF Chat	Spatial Clustering of Array CGH Features in Combination with Hierarchical Multiple Testing	2010	Kyung In Kim Étienne Roquain Mark A. van de Wiel
+ PDF Chat	Optimal weighting for false discovery rate control	2009	Étienne Roquain Mark A. van de Wiel
+	Comments on: Control of the false discovery rate under dependence using the bootstrap and subsampling	2008	José A. Ferreira Mark A. van de Wiel
+ PDF Chat	Effects of dependence in high-dimensional multiple testing problems	2008	Kyung In Kim Mark A. van de Wiel
+	A nonparametric control chart based on the Mann-Whitney statistic	2008	S. Chakraborti Mark A. van de Wiel
+	Implementing a Class of Permutation Tests: The<b>coin</b>Package	2008	Torsten Hothorn Kurt Hornik Mark A. van de Wiel Achim Zeileis
+	SOME COMMENTS ON FALSE DISCOVERY RATE	2007	Avner Bar‐Hen Kyung In Kim Mark A. van de Wiel
+ PDF Chat	A Lego System for Conditional Inference	2006	Torsten Hothorn Kurt Hornik Mark A. van de Wiel Achim Zeileis
+	A Note on Sample Size Determination for a Nonparametric Test of Location	2006	S. Chakraborti Bang Hong Mark A. van de Wiel
+	The null distribution of Kendall's rank correlation statistic in the presence of ties	2005	Mark A. van de Wiel
+	coin: Conditional Inference Procedures in a Permutation Test Framework	2005	Torsten Hothorn Henric Winell Kurt Hornik Mark A. van de Wiel Achim Zeileis
+	Exact null distributions of distribution-free quadratic t-sample statistics	2003	A. Di Bucchianico Mark A. van de Wiel
+	Exact null distributions of quadratic distribution-free statistics for two-way classification	2003	Mark A. van de Wiel
+	Exact Distributions of Multiple Comparisons Rank Statistics	2002	Mark A. van de Wiel
+	The split-up algorithm: a fast symbolic method for computing p-values of distribution-free statistics	2001	Mark A. van de Wiel
+	Fast computation of the exact null distribution of Spearman's ρ and Page's L statistic for samples with and without ties	2001	Mark A. van de Wiel A. Di Bucchianico
+	EXACT NON-NULL DISTRIBUTIONS OF RANK STATISTICS	2001	Mark A. van de Wiel
+	Edgeworth expansions with exact cumulants for two-sample linear rank statistics	1998	Mark A. van de Wiel

Common Coauthors

Coauthor	Papers Together
Wessel N. van Wieringen	15
Aad van der Vaart	13
Gwenaël G. R. Leday	11
Carel F.W. Peeters	10
Mirrelijn M. van Nee	9
Thomas Klausch	8
Magnus Münch	8
Gino B. Kpogbezan	7
Dennis E. te Beest	7
Armin Rauschenberger	6
Lodewyk F.A. Wessels	5
Torsten Hothorn	5
Achim Zeileis	5
Kurt Hornik	5
Steven W. Mes	5
Saskia M. Wilting	4
Martijn W. Heymans	4
Jeroen M. Goedhart	4
Jurre R. Veerman	3
Henric Winell	3
Johannes Berkhof	3
Kyung In Kim	3
Wina Verlaat	3
Jeroen Hoogland	3
Renée X. de Menezes	3
Ruud H. Brakenhoff	3
Mathisca C. M. de Gunst	3
Tim van de Brug	3
Tonje G. Lien	3
Pim de Graaf	2
Enrico Glaab	2
Thomas Koopman	2
Floris H. P. van Velden	2
S. Chakraborti	2
Veerle M.H. Coupé	2
Jonas A. Castelijns	2
Anne‐Laure Boulesteix	2
Marianne A. Jonker	2
A. Di Bucchianico	2
Étienne Roquain	2
Astrid Zierer	2
Eddymurphy U. Akwiwu	2
Matteo Amestoy	2
Roland M. Martens	2
Zied Landoulsi	2
Simone Wahl	2
Caroline Übelhör	2
Ronald Boellaard	2
Francisca A. de Leeuw	1
Thomas Hankemeier	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+ PDF Chat	Better prediction by use of co‐data: adaptive group‐regularized ridge regression	2015	Mark A. van de Wiel Tonje G. Lien Wina Verlaat Wessel N. van Wieringen Saskia M. Wilting	18
+	Gene network reconstruction using global-local shrinkage priors	2017	Gwenaël G. R. Leday Mathisca C. M. de Gunst Gino B. Kpogbezan Aad van der Vaart Wessel N. van Wieringen Mark A. van de Wiel	11
+	Regularization Paths for Generalized Linear Models via Coordinate Descent.	2010	Jerome H. Friedman Trevor Hastie Rob Tibshirani	10
+	Regression Shrinkage and Selection Via the Lasso	1996	Robert Tibshirani	10
+	Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations	2009	Håvard Rue Sara Martino Nicolás Chopin	10
+ PDF Chat	The Group Lasso for Logistic Regression	2008	Lukas Meier Sara van de Geer Peter Bühlmann	10
+ PDF Chat	The Adaptive Lasso and Its Oracle Properties	2006	Hui Zou	9
+	Ridge Regression: Biased Estimation for Nonorthogonal Problems	2000	Arthur E. Hoerl Robert W. Kennard	9
+	Regularization Paths for Generalized Linear Models via Coordinate Descent	2010	Jerome H. Friedman Trevor Hastie Robert Tibshirani	9
+ PDF Chat	Consistent High-Dimensional Bayesian Variable Selection via Penalized Credible Regions	2012	Howard D. Bondell Brian J. Reich	8
+	Variational Inference: A Review for Statisticians	2017	David M. Blei Alp Kucukelbir Jon McAuliffe	8
+ PDF Chat	Weighted Lasso with Data Integration	2011	Linn Cecilie Bergersen Ingrid K. Glad Heidi Lyng	7
+ PDF Chat	Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models	2010	Simon N. Wood	7
+	Ridge Regression: Biased Estimation for Nonorthogonal Problems	1970	Arthur E. Hoerl Robert W. Kennard	7
+	Empirical Bayes Gibbs sampling	2001	George Casella	6
+ PDF Chat	Learning from a lot: Empirical Bayes for high‐dimensional model‐based prediction	2018	Mark A. van de Wiel Dennis E. te Beest Magnus Münch	6
+	Ridge Estimators in Logistic Regression	1992	Saskia le Cessie Hans C. van Houwelingen	6
+ PDF Chat	Scalable Variational Inference for Bayesian Variable Selection in Regression, and Its Accuracy in Genetic Association Studies	2012	Peter Carbonetto Matthew Stephens	6
+ PDF Chat	Ridge estimation of inverse covariance matrices from high-dimensional data	2016	Wessel N. van Wieringen Carel F.W. Peeters	6
+	The Bayesian Lasso	2008	Trevor Park George Casella	6
+ PDF Chat	Explaining Variational Approximations	2010	John T. Ormerod M. P. Wand	6
+	Sparse inverse covariance estimation with the graphical lasso	2007	Jerome H. Friedman Trevor Hastie R. Tibshirani	5
+	<i>L</i><sub>1</sub> Penalized Estimation in the Cox Proportional Hazards Model	2009	Jelle J. Goeman	5
+ PDF Chat	Model Selection and Estimation in Regression with Grouped Variables	2005	Ming Yuan Yi Lin	5
+	Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing	1995	Yoav Benjamini Yosef Hochberg	5
+	The horseshoe estimator for sparse signals	2010	Carla M. Carvalho Nick Polson James G. Scott	5
+ PDF Chat	Flexible co‐data learning for high‐dimensional prediction	2021	Mirrelijn M. van Nee Lodewyk F.A. Wessels Mark A. van de Wiel	5
+ PDF Chat	The Bayesian elastic net	2010	Qing Li Nan Lin	5
+	Adaptive group-regularized logistic elastic net regression	2019	Magnus Münch Carel F.W. Peeters Aad van der Vaart Mark A. van de Wiel	5
+ PDF Chat	Bayesian Inference for Logistic Models Using Pólya–Gamma Latent Variables	2013	Nicholas G. Polson James G. Scott Jesse Windle	5
+	A Sparse-Group Lasso	2012	Noah Simon Jerome H. Friedman Trevor Hastie Robert Tibshirani	5
+ PDF Chat	Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures	2014	Isabella Zwiener Barbara Frisch Harald Binder	5
+	Laplace Approximation of High Dimensional Integrals	1995	Zhenming Shun Peter McCullagh	5
+ PDF Chat	Dimensionality Reduction for Supervised Learning With Reproducing Kernel Hilbert Spaces	2003	Kenji Fukumizu Francis R. Bach Michael I. Jordan	5
+	The Elements of Statistical Learning	2001	Trevor Hastie J. Friedman Robert Tibshirani	5
+	Efficient approximate <i>k</i>‐fold and leave‐one‐out cross‐validation for ridge regression	2013	Rosa J. Meijer Jelle J. Goeman	5
+ PDF Chat	Improved high-dimensional prediction with Random Forests by the use of co-data	2017	Dennis E. te Beest Steven W. Mes Saskia M. Wilting Ruud H. Brakenhoff Mark A. van de Wiel	5
+ PDF Chat	Bayesian Structure Learning in Sparse Gaussian Graphical Models	2015	Reza Mohammadi Ernst C. Wit	4
+ PDF Chat	The positive false discovery rate: a Bayesian interpretation and the q-value	2003	John D. Storey	4
+ PDF Chat	Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective	2015	P. Richard Hahn Carlos M. Carvalho	4
+ PDF Chat	The horseshoe estimator: Posterior concentration around nearly black vectors	2014	Stéphanie van der Pas B. J. K. Kleijn Aad van der Vaart	4
+	Constructing exact significance tests with restricted randomization rules	1988	Cyrus R. Mehta Nitin R. Patel L. J. Wei	4
+	Penalized Normal Likelihood and Ridge Regularization of Correlation and Covariance Matrices	2008	David I. Warton	4
+ PDF Chat	Selection and estimation for mixed graphical models	2014	Shuai Chen Daniela Witten Ali Shojaie	4
+ PDF Chat	Adaptive penalization in high-dimensional regression and classification with external covariates using variational Bayes	2019	Britta Velten Wolfgang Huber	4
+ PDF Chat	A well-conditioned estimator for large-dimensional covariance matrices	2003	Olivier Ledoit Michael Wolf	4
+	High-dimensional graphs and variable selection with the Lasso	2006	Nicolai Meinshausen Peter Bühlmann	4
+	Graphical Models in Applied Multivariate Statistics	1991	Colin Goodall Joe Whittaker	4
+	Empirical Bayesian Estimators for a Poisson Process Propagated in Time	1999	S.H. Heisterkam Hans C. van Houwelingen Angela M. Downs	4
+	Adaptive Lasso for sparse high-dimensional regression models	2008	Jian Huang Shuangge Ma Cun Hui Zhang	4