E-LIB Suche - Ergebnisse für: Wilms, Ines

1

Monitoring Machine Learning Forecasts for Platform Data Str..:

Rombouts, Jeroen ; Wilms, Ines
http://arxiv.org/abs/2401.09144. , 2024

Link: http://arxiv.org/abs/240..

2

Tree-based Forecasting of Day-ahead Solar Power Generation ..:

Berlanger, Nick ; van Ophoven, Noah ; Verdonck, Tim.
http://arxiv.org/abs/2312.00090. , 2023

Link: http://arxiv.org/abs/231..

3

Hierarchical Regularizers for Reverse Unrestricted Mixed Da..:

Hecq, Alain ; Ternes, Marie ; Wilms, Ines
http://arxiv.org/abs/2301.10592. , 2023

Link: http://arxiv.org/abs/230..

4

Identifying Important Pairwise Logratios in Compositional D..:

Nesrstová, Viktorie ; Wilms, Ines ; Hron, Karel.
http://arxiv.org/abs/2311.13911. , 2023

Link: http://arxiv.org/abs/231..

5

Fast Forecasting of Unstable Data Streams for On-Demand Ser..:

Hu, Yu Jeffrey ; Rombouts, Jeroen ; Wilms, Ines
http://arxiv.org/abs/2303.01887. , 2023

Link: http://arxiv.org/abs/230..

6

Sparse High-Dimensional Vector Autoregressive Bootstrap:

Adamek, Robert ; Smeekes, Stephan ; Wilms, Ines
http://arxiv.org/abs/2302.01233. , 2023

Link: http://arxiv.org/abs/230..

7

Sparse Identification and Estimation of Large-Scale Vector ..:

Wilms, Ines ; Basu, Sumanta ; Bien, Jacob.
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281743/. , 2023

Link: http://www.ncbi.nlm.nih...

8

Detecting Anti-dumping Circumvention: A Network Approach:

Barbaglia, Luca ; Croux, Christophe ; Wilms, Ines
http://arxiv.org/abs/2207.05394. , 2022

Link: http://arxiv.org/abs/220..

9

Tree-based Node Aggregation in Sparse Graphical Models:

Wilms, Ines ; Bien, Jacob
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10805464/. , 2022

Link: http://www.ncbi.nlm.nih...

10

Graphical Influence Diagnostics for Changepoint Models:

Wilms, Ines ; Killick, Rebecca ; Matteson, David S
Wilms , I , Killick , R & Matteson , D S 2022 , ' Graphical Influence Diagnostics for Changepoint Models ' , Journal of Computational and Graphical Statistics . https://doi.org/10.1080/10618600.2021.2000873. , 2022

Link: https://cris.maastrichtu..

11

Graphical Influence Diagnostics for Changepoint Models:

Wilms, Ines ; Killick, Rebecca ; Matteson, David S
https://eprints.lancs.ac.uk/id/eprint/161559/1/2107.10572v1.pdf. , 2022

Link: https://eprints.lancs.ac..

12

The Influence Function of Graphical Lasso Estimators:

Louvet, Gaëtan ; Raymaekers, Jakob ; Van Bever, Germain.
http://arxiv.org/abs/2209.07374. , 2022

Link: http://arxiv.org/abs/220..

13

Local Projection Inference in High Dimensions:

Adamek, Robert ; Smeekes, Stephan ; Wilms, Ines
http://arxiv.org/abs/2209.03218. , 2022

Link: http://arxiv.org/abs/220..

14

Regularized Predictive Models for Beef Eating Quality of In..:

Tarr, Garth ; Wilms, Ines
http://arxiv.org/abs/2207.02362. , 2022

Link: http://arxiv.org/abs/220..

15

Hierarchical Regularizers for Mixed-Frequency Vector Autore..:

Hecq, Alain ; Ternes, Marie ; Wilms, Ines
http://arxiv.org/abs/2102.11780. , 2021

Link: http://arxiv.org/abs/210..