activity
20192021
collaborators

6 papers

stat.ME2021

RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data

Erica Ponzi, Magne Thoresen, Abhik Ghosh

With increasing availability of high dimensional, multi-source data, the identification of joint and data specific patterns of variability has become a subject of interest in many…

stat.ME2020

On optimal two-stage testing of multiple mediators

Vera Djordjilović, Jesse Hemerik, Magne Thoresen

Mediation analysis in high-dimensional settings often involves identifying potential mediators among a large number of measured variables. For this purpose, a two-step familywise e…

stat.ME2020

A robust variable screening procedure for ultra-high dimensional data

Abhik Ghosh, Magne Thoresen

Variable selection in ultra-high dimensional regression problems has become an important issue. In such situations, penalized regression models may face computational problems and…

stat.ME2020

Permutation testing in high-dimensional linear models: an empirical investigation

Jesse Hemerik, Magne Thoresen, Livio Finos

Permutation testing in linear models, where the number of nuisance coefficients is smaller than the sample size, is a well-studied topic. The common approach of such tests is to pe…

stat.ME2019

Optimal two-stage testing of multiple mediators

Vera Djordjilović, Jesse Hemerik, Magne Thoresen

Mediation analysis in high-dimensional settings often involves identifying potential mediators among a large number of measured variables. For this purpose, a two step familywise e…

stat.ME2019

Consistent Fixed-Effects Selection in Ultra-high dimensional Linear Mixed Models with Error-Covariate Endogeneity

Abhik Ghosh, Magne Thoresen

Recently, applied sciences, including longitudinal and clustered studies in biomedicine require the analysis of ultra-high dimensional linear mixed effects models where we need to…