Ines Wilms
Names
Identifer
Contact
Affiliations
-
Maastricht University
/ School of Business and Economics
/ Vakgroep Kwantitatieve Economie
Research profile
author of:
- Commodity Dynamics: A Sparse Multi-class Approach (RePEc:arx:papers:1604.01224)
by Luca Barbaglia & Ines Wilms & Christophe Croux - Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach (RePEc:arx:papers:1708.02073)
by Luca Barbaglia & Christophe Croux & Ines Wilms - Lasso Inference for High-Dimensional Time Series (RePEc:arx:papers:2007.10952)
by Robert Adamek & Stephan Smeekes & Ines Wilms - bootUR: An R Package for Bootstrap Unit Root Tests (RePEc:arx:papers:2007.12249)
by Stephan Smeekes & Ines Wilms - Tree-based Node Aggregation in Sparse Graphical Models (RePEc:arx:papers:2101.12503)
by Ines Wilms & Jacob Bien - Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions (RePEc:arx:papers:2102.11780)
by Alain Hecq & Marie Ternes & Ines Wilms - Detecting Anti-dumping Circumvention: A Network Approach (RePEc:arx:papers:2207.05394)
by Luca Barbaglia & Christophe Croux & Ines Wilms - Local Projection Inference in High Dimensions (RePEc:arx:papers:2209.03218)
by Robert Adamek & Stephan Smeekes & Ines Wilms - Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions (RePEc:arx:papers:2301.10592)
by Alain Hecq & Marie Ternes & Ines Wilms - Sparse High-Dimensional Vector Autoregressive Bootstrap (RePEc:arx:papers:2302.01233)
by Robert Adamek & Stephan Smeekes & Ines Wilms - Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms (RePEc:arx:papers:2303.01887)
by Yu Jeffrey Hu & Jeroen Rombouts & Ines Wilms - Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning (RePEc:arx:papers:2402.09033)
by Jeroen Rombouts & Marie Ternes & Ines Wilms - Transmission Channel Analysis in Dynamic Models (RePEc:arx:papers:2405.18987)
by Enrico Wegner & Lenard Lieb & Stephan Smeekes & Ines Wilms - Vector AutoRegressive Moving Average Models: A Review (RePEc:arx:papers:2406.19702)
by Marie-Christine Duker & David S. Matteson & Ruey S. Tsay & Ines Wilms - Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach (RePEc:arx:papers:2407.07973)
by Alain Hecq & Ivan Ricardo & Ines Wilms - Multiclass vector auto‐regressive models for multistore sales data (RePEc:bla:jorssc:v:67:y:2018:i:2:p:435-452)
by Ines Wilms & Luca Barbaglia & Christophe Croux - Discussion of ‘Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models’ (RePEc:bla:scjsta:v:43:y:2016:i:2:p:353-356)
by Christophe Croux & Ines Wilms - Lasso inference for high-dimensional time series (RePEc:eee:econom:v:235:y:2023:i:2:p:1114-1143)
by Adamek, Robert & Smeekes, Stephan & Wilms, Ines - The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach (RePEc:eee:ejores:v:254:y:2016:i:1:p:138-147)
by Wilms, Ines & Gelper, Sarah & Croux, Christophe - Sparse regression for large data sets with outliers (RePEc:eee:ejores:v:297:y:2022:i:2:p:782-794)
by Bottmer, Lea & Croux, Christophe & Wilms, Ines - Commodity dynamics: A sparse multi-class approach (RePEc:eee:eneeco:v:60:y:2016:i:c:p:62-72)
by Barbaglia, Luca & Wilms, Ines & Croux, Christophe - Volatility spillovers in commodity markets: A large t-vector autoregressive approach (RePEc:eee:eneeco:v:85:y:2020:i:c:s0140988319303500)
by Barbaglia, Luca & Croux, Christophe & Wilms, Ines - Forecasting using sparse cointegration (RePEc:eee:intfor:v:32:y:2016:i:4:p:1256-1267)
by Wilms, Ines & Croux, Christophe - Multivariate volatility forecasts for stock market indices (RePEc:eee:intfor:v:37:y:2021:i:2:p:484-499)
by Wilms, Ines & Rombouts, Jeroen & Croux, Christophe - Identifying Demand Effects in a Large Network of Product Categories (RePEc:eee:jouret:v:92:y:2016:i:1:p:25-39)
by Gelper, Sarah & Wilms, Ines & Croux, Christophe - Robust sparse canonical correlation analysis (RePEc:ete:kbiper:472948)
by Ines Wilms & Christophe Croux - The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach (RePEc:ete:kbiper:504661)
by Ines Wilms & Sarah Gelper & Christophe Croux - An algorithm for the multivariate group lasso with covariance estimation (RePEc:ete:kbiper:516983)
by Ines Wilms & Christophe Croux - Commodity dynamics: a sparse multi-class approach (RePEc:ete:kbiper:538113)
by Luca Barbaglia & Ines Wilms & Christophe Croux - Multi-class vector autoregressive models for multi-store sales data (RePEc:ete:kbiper:540947)
by Ines Wilms & Luca Barbaglia & Christophe Croux - Lasso-based forecast combinations for forecasting realized variances (RePEc:ete:kbiper:553087)
by Ines Wilms & Jeroen Rombouts & Christophe Croux - Cellwise robust regularized discriminant analysis (RePEc:ete:kbiper:563648)
by Stéphanie Aerts & Ines Wilms - Volatility spillovers and heavy tails: a large t-Vector AutoRegressive approach (RePEc:ete:kbiper:590528)
by Luca Barbaglia & Christophe Croux & Ines Wilms - Local projection inference in high dimensions (RePEc:oup:emjrnl:v:27:y:2024:i:3:p:323-342.)
by Robert Adamek & Stephan Smeekes & Ines Wilms - White heteroscedasticty testing after outlier removal (RePEc:oxf:wpaper:853)
by Vanessa Berenguer Rico & Ines Wilms - Heteroscedasticity testing after outlier removal (RePEc:taf:emetrv:v:40:y:2021:i:1:p:51-85)
by Vanessa Berenguer-Rico & Ines Wilms - An algorithm for the multivariate group lasso with covariance estimation (RePEc:taf:japsta:v:45:y:2018:i:4:p:668-681)
by I. Wilms & C. Croux - Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages (RePEc:taf:jnlasa:v:118:y:2023:i:541:p:571-582)
by Ines Wilms & Sumanta Basu & Jacob Bien & David S. Matteson