Ines Wilms - researchr alias

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Viewing Publication 1 - 10 from 10

2025

Fast Forecasting of Unstable Data Streams for On-Demand Service PlatformsYu (Jeffrey) Hu, Jeroen V. K. Rombouts, Ines Wilms. isr, 36(1):552-571, 2025. [doi]

2023

R Package for Bootstrap Unit Root TestsStephan Smeekes, Ines Wilms. jstatsoft, 106(12), 2023. [doi]

2022

Sparse regression for large data sets with outliersLea Bottmer, Christophe Croux, Ines Wilms. eor, 297(2):782-794, 2022. [doi]

Hierarchical Regularizers for Mixed-Frequency Vector AutoregressionsAlain Hecq, Marie Ternes, Ines Wilms. jcgs, 31(4):1076-1090, October 2022. [doi]

Graphical Influence Diagnostics for Changepoint ModelsInes Wilms, Rebecca Killick, David S. Matteson. jcgs, 31(3):753-765, July 2022. [doi]

Tree-based Node Aggregation in Sparse Graphical ModelsInes Wilms, Jacob Bien. jmlr, 23, 2022. [doi]

2020

High Dimensional Forecasting via Interpretable Vector AutoregressionWilliam B. Nicholson, Ines Wilms, Jacob Bien, David S. Matteson. jmlr, 21, 2020. [doi]

2017

Cellwise robust regularized discriminant analysisStephanie Aerts, Ines Wilms. sadm, 10(6):436-447, 2017. [doi]

2016

The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approachInes Wilms, Sarah Gelper, Christophe Croux. eor, 254(1):138-147, 2016. [doi]

Robust sparse canonical correlation analysisInes Wilms, Christophe Croux. bmcsb, 10:72, 2016. [doi]

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