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01/24/2023
Think before you shrink: Alternatives to default shrinkage methods can improve prediction accuracy, calibration and coverage
While shrinkage is essential in high-dimensional settings, its use for l...
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12/16/2022
Penalised regression with multiple sources of prior effects
In many high-dimensional prediction or classification tasks, complementa...
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06/08/2022
Estimation of Predictive Performance in High-Dimensional Data Settings using Learning Curves
In high-dimensional prediction settings, it remains challenging to relia...
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05/16/2022
ecpc: An R-package for generic co-data models for high-dimensional prediction
High-dimensional prediction considers data with more variables than samp...
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10/06/2021
A Bayesian accelerated failure time model for interval-censored three-state screening outcomes
Women infected by the Human papilloma virus are at an increased risk to ...
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04/06/2021
Semi-supervised empirical Bayes group-regularized factor regression
The features in high dimensional biomedical prediction problems are ofte...
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01/11/2021
Fast marginal likelihood estimation of penalties for group-adaptive elastic net
Nowadays, clinical research routinely uses omics data, such as gene expr...
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05/19/2020
Fast cross-validation for multi-penalty ridge regression
Prediction based on multiple high-dimensional data types needs to accoun...
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05/08/2020
Flexible co-data learning for high-dimensional prediction
Clinical research often focuses on complex traits in which many variable...
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03/27/2019
Stable prediction with radiomics data
Motivation: Radiomics refers to the high-throughput mining of quantitati...
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02/07/2019
Estimation of variance components, heritability and the ridge penalty in high-dimensional generalized linear models
For high-dimensional linear regression models, we review and compare sev...
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01/29/2019
Incorporating prior information and borrowing information in high-dimensional sparse regression using the horseshoe and variational Bayes
We introduce a sparse high-dimensional regression approach that can inco...
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09/18/2018
Estimating Bayesian Optimal Treatment Regimes for Dichotomous Outcomes using Observational Data
Optimal treatment regimes (OTR) are individualised treatment assignment ...
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05/23/2018
Detecting SNPs with interactive effects on a quantitative trait
Here we propose a test to detect effects of single nucleotide polymorphi...
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05/01/2018
Adaptive group-regularized logistic elastic net regression
In high-dimensional data settings, additional information on the feature...
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08/14/2016