ines wilms

ines wilms

Universiteit Maastricht

H-index: 15

Europe-Netherlands

About ines wilms

ines wilms, With an exceptional h-index of 15 and a recent h-index of 14 (since 2020), a distinguished researcher at Universiteit Maastricht, specializes in the field of Statistics, High-dimensional analysis, Time series analysis, Forecasting.

His recent articles reflect a diverse array of research interests and contributions to the field:

Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning

Monitoring Machine Learning Forecasts for Platform Data Streams

The Influence Function of Graphical Lasso Estimators

Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological Features

Identifying Important Pairwise Logratios in Compositional Data with Sparse Principal Component Analysis

Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms

Sparse High-Dimensional Vector Autoregressive Bootstrap

Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions

ines wilms Information

University

Position

___

Citations(all)

676

Citations(since 2020)

565

Cited By

259

hIndex(all)

15

hIndex(since 2020)

14

i10Index(all)

17

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

ines wilms Skills & Research Interests

Statistics

High-dimensional analysis

Time series analysis

Forecasting

Top articles of ines wilms

Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning

arXiv preprint arXiv:2402.09033

2024/2/14

Ines Wilms
Ines Wilms

H-Index: 8

Monitoring Machine Learning Forecasts for Platform Data Streams

arXiv preprint arXiv:2401.09144

2024/1/17

Ines Wilms
Ines Wilms

H-Index: 8

The Influence Function of Graphical Lasso Estimators

Econometrics and Statistics

2023

Tree-based Forecasting of Day-ahead Solar Power Generation from Granular Meteorological Features

arXiv preprint arXiv:2312.00090

2023/11/30

Ines Wilms
Ines Wilms

H-Index: 8

Identifying Important Pairwise Logratios in Compositional Data with Sparse Principal Component Analysis

arXiv preprint arXiv:2311.13911

2023/11/23

Ines Wilms
Ines Wilms

H-Index: 8

Peter Filzmoser
Peter Filzmoser

H-Index: 51

Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms

Available at SSRN 4346040

2023/2/2

Yu Jeffrey Hu
Yu Jeffrey Hu

H-Index: 19

Ines Wilms
Ines Wilms

H-Index: 8

Sparse High-Dimensional Vector Autoregressive Bootstrap

arXiv preprint arXiv:2302.01233

2023/2/2

Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions

arXiv preprint arXiv:2301.10592

2023/1/25

Alain Hecq
Alain Hecq

H-Index: 11

Ines Wilms
Ines Wilms

H-Index: 8

Data Science in Science: Special Issue on Data Science in Environmental and Climate Sciences

2023/12/31

Principal Balances of Compositional Data for Regression and Classification using Partial Least Squares

arXiv preprint arXiv:2211.01686

2022/11/3

Local Projection Inference in High Dimensions

arXiv preprint arXiv:2209.03218

2022/9/7

Detecting Anti-dumping Circumvention: A Network Approach

arXiv preprint arXiv:2207.05394

2022/7/12

Ines Wilms
Ines Wilms

H-Index: 8

Sparse regression for large data sets with outliers

European Journal of Operational Research

2022/3/1

Ines Wilms
Ines Wilms

H-Index: 8

Regularized Predictive Models for Beef Eating Quality of Individual Meals

Data Science in Science

2022

Ines Wilms
Ines Wilms

H-Index: 8

Graphical Influence Diagnostics for Changepoint Models

Journal of Computational and Graphical Statistics

2022/7/3

Ines Wilms
Ines Wilms

H-Index: 8

Rebecca Killick
Rebecca Killick

H-Index: 14

Hierarchical regularizers for mixed-frequency vector autoregressions

Journal of Computational and Graphical Statistics

2022

Alain Hecq
Alain Hecq

H-Index: 11

Ines Wilms
Ines Wilms

H-Index: 8

Tree-based Node Aggregation in Sparse Graphical Models

Journal of Machine Learning Research

2022

Ines Wilms
Ines Wilms

H-Index: 8

Jacob Bien
Jacob Bien

H-Index: 15

bigtime: Sparse Estimation of Large Time Series Models

2021/8/9

Sparse identification and estimation of large-scale vector autoregressive moving averages

Journal of the American Statistical Association

2021

changepoint. influence: Package to Calculate the Influence of the Data on a Changepoint Segmentation

2021/8/4

Rebecca Killick
Rebecca Killick

H-Index: 14

Ines Wilms
Ines Wilms

H-Index: 8

See List of Professors in ines wilms University(Universiteit Maastricht)

Co-Authors

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