Shankar, R., Wilms, I., Raymaekers, J., & Tarr, G. (2026). Outlier detection in state-space models using mean-shift penalisation. Statistics and Computing, 36(4), Article 176. https://doi.org/10.1007/s11222-026-10935-4
Touw, D. J. W., Alfons, A., Groenen, P. J. F., & Wilms, I. (2026). Clusterpath Gaussian Graphical Modeling. Journal of Computational and Graphical Statistics. Advance online publication. https://doi.org/10.1080/10618600.2026.2653764
Wals, S., Grewal, D., Wilms, I., Hilken, T., Briassouli, A., & Wetzels, M. (2026). The dynamic effects of visual complexity and scene cuts on viewer attention. Journal of the Academy of Marketing Science, 54(2), 596-617. https://doi.org/10.1007/s11747-025-01137-x
Hecq, A., Ricardo, I., & Wilms, I. (2026). Decomposing co-movements in matrix-valued time series: A pseudo-structural reduced rank approach. Econometrics and Statistics. Advance online publication. https://doi.org/10.1016/j.ecosta.2026.07.002
Girolimetto, D., Rombouts, J., Wilms, I., & Yang, Y. (2026). FoReco and FoRecoML: A Unified Toolbox for Forecast Reconciliation in R. Cornell University - arXiv. arXiv.org No. 2604.27696 https://doi.org/10.48550/arXiv.2604.27696
Corillon, M., Smeekes, S., & Wilms, I. (2026). Sparse Tree-Based Aggregation for Time Series Regressions. Cornell University - arXiv. arXiv.org No. 2606.03665 https://doi.org/10.48550/arXiv.2606.03665
Louvet, G., Raymaekers, J., Van Bever, G., & Wilms, I. (2026). The Influence Function of Graphical Lasso Estimators. Econometrics and Statistics, 39, 268-280. https://doi.org/10.1016/j.ecosta.2023.03.004
Schaap, E., Mahr, D., Wilms, I., Klingwort, J., & Grewal, D. (2026). Why more isn’t always better: Examining the effects of network density on firms’ likelihood of new product innovation. Journal of Business Research, 212, Article 116192. https://doi.org/10.1016/j.jbusres.2026.116192
Hecq, A., Ternes, M., & Wilms, I. (2025). Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions. Journal of Forecasting, 44(6), 1946-1968. https://doi.org/10.1002/for.3277