1 citations · 1 across the 6 of their papers we have counts for
7 papers
A Semiparametric Nonlinear Mixed Effects Model with Penalized Splines Using Automatic Differentiation
Matteo D'Alessandro, Magne Thoresen, Øystein Sørensen
We present an estimation procedure for nonlinear mixed-effects models in which the population trajectory is represented by penalized splines and adapted to individuals via subject-…
False Discovery Rate Control via Bayesian Mirror Statistic
Marco Molinari, Magne Thoresen
Simultaneously performing variable selection and inference in high-dimensional models is an open challenge in statistics and machine learning. The increasing availability of vast a…
Methods of Selective Inference for Linear Mixed Models: a Review and Empirical Comparison
Matteo D'Alessandro, Magne Thoresen
Selective inference aims at providing valid inference after a data-driven selection of models or hypotheses. It is essential to avoid overconfident results and replicability issues…
Bad estimation, good prediction: the Lasso in dense regimes
Andrea Bratsberg, Magne Thoresen, Jelle J. Goeman
For high-dimensional omics data, sparsity-inducing regularization methods such as the Lasso are widely used and often yield strong predictive performance, even in settings when the…
Methods for differential network estimation: an empirical comparison
Anna Plaksienko, Magne Thoresen, Vera Djordjilović
We provide a review and a comparison of methods for differential network estimation in Gaussian graphical models with focus on structure learning. We consider the case of two datas…
Comparison of the LASSO and Integrative LASSO with Penalty Factors (IPF-LASSO) methods for multi-omics data: Variable selection with Type I error control
Charlotte Castel, Zhi Zhao, Magne Thoresen
Variable selection in relation to regression modeling has constituted a methodological problem for more than 60 years. Especially in the context of high-dimensional regression, dev…
Conditional variable screening for ultra-high dimensional longitudinal data with time interactions
Andrea Bratsberg, Abhik Ghosh, Magne Thoresen
In recent years we have been able to gather large amounts of genomic data at a fast rate, creating situations where the number of variables greatly exceeds the number of observatio…