Details about Ines Wilms
Access statistics for papers by Ines Wilms.
Last updated 2024-11-07. Update your information in the RePEc Author Service.
Short-id: pwi441
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Working Papers
2024
- Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning
Papers, arXiv.org
- Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms
Papers, arXiv.org
- Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions
Papers, arXiv.org View citations (1)
- Local Projection Inference in High Dimensions
Papers, arXiv.org 
See also Journal Article Local projection inference in high dimensions, The Econometrics Journal, Royal Economic Society (2024) (2024)
- Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach
Papers, arXiv.org
- Transmission Channel Analysis in Dynamic Models
Papers, arXiv.org
- Vector AutoRegressive Moving Average Models: A Review
Papers, arXiv.org
2023
- Sparse High-Dimensional Vector Autoregressive Bootstrap
Papers, arXiv.org
2022
- Detecting Anti-dumping Circumvention: A Network Approach
Papers, arXiv.org
- Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions
Papers, arXiv.org View citations (2)
- Lasso Inference for High-Dimensional Time Series
Papers, arXiv.org View citations (4)
See also Journal Article Lasso inference for high-dimensional time series, Journal of Econometrics, Elsevier (2023) View citations (6) (2023)
- bootUR: An R Package for Bootstrap Unit Root Tests
Papers, arXiv.org View citations (1)
2021
- Tree-based Node Aggregation in Sparse Graphical Models
Papers, arXiv.org
2018
- White heteroscedasticty testing after outlier removal
Economics Series Working Papers, University of Oxford, Department of Economics View citations (5)
2017
- Cellwise robust regularized discriminant analysis
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven
- Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach
Papers, arXiv.org 
Also in Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven (2017) View citations (1)
2016
- Commodity Dynamics: A Sparse Multi-class Approach
Papers, arXiv.org View citations (8)
Also in Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven (2016) 
See also Journal Article Commodity dynamics: A sparse multi-class approach, Energy Economics, Elsevier (2016) View citations (8) (2016)
- Lasso-based forecast combinations for forecasting realized variances
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven
- Multi-class vector autoregressive models for multi-store sales data
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven 
See also Journal Article Multiclass vector auto‐regressive models for multistore sales data, Journal of the Royal Statistical Society Series C, Royal Statistical Society (2018) View citations (1) (2018)
2015
- An algorithm for the multivariate group lasso with covariance estimation
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven 
See also Journal Article An algorithm for the multivariate group lasso with covariance estimation, Journal of Applied Statistics, Taylor & Francis Journals (2018) View citations (3) (2018)
- The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven 
See also Journal Article The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach, European Journal of Operational Research, Elsevier (2016) View citations (13) (2016)
2014
- Robust sparse canonical correlation analysis
Working Papers of Department of Decision Sciences and Information Management, Leuven, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven
Journal Articles
2024
- Local projection inference in high dimensions
The Econometrics Journal, 2024, 27, (3), 323-342 
See also Working Paper Local Projection Inference in High Dimensions, Papers (2024) (2024)
2023
- Lasso inference for high-dimensional time series
Journal of Econometrics, 2023, 235, (2), 1114-1143 View citations (6)
See also Working Paper Lasso Inference for High-Dimensional Time Series, Papers (2022) View citations (4) (2022)
- Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages
Journal of the American Statistical Association, 2023, 118, (541), 571-582 View citations (1)
2022
- Sparse regression for large data sets with outliers
European Journal of Operational Research, 2022, 297, (2), 782-794 View citations (7)
2021
- Heteroscedasticity testing after outlier removal
Econometric Reviews, 2021, 40, (1), 51-85 View citations (1)
- Multivariate volatility forecasts for stock market indices
International Journal of Forecasting, 2021, 37, (2), 484-499 View citations (19)
2020
- Volatility spillovers in commodity markets: A large t-vector autoregressive approach
Energy Economics, 2020, 85, (C) View citations (40)
2018
- An algorithm for the multivariate group lasso with covariance estimation
Journal of Applied Statistics, 2018, 45, (4), 668-681 View citations (3)
See also Working Paper An algorithm for the multivariate group lasso with covariance estimation, Working Papers of Department of Decision Sciences and Information Management, Leuven (2015) (2015)
- Multiclass vector auto‐regressive models for multistore sales data
Journal of the Royal Statistical Society Series C, 2018, 67, (2), 435-452 View citations (1)
See also Working Paper Multi-class vector autoregressive models for multi-store sales data, Working Papers of Department of Decision Sciences and Information Management, Leuven (2016) (2016)
2016
- Commodity dynamics: A sparse multi-class approach
Energy Economics, 2016, 60, (C), 62-72 View citations (8)
See also Working Paper Commodity Dynamics: A Sparse Multi-class Approach, Papers (2016) View citations (8) (2016)
- Discussion of ‘Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models’
Scandinavian Journal of Statistics, 2016, 43, (2), 353-356
- Forecasting using sparse cointegration
International Journal of Forecasting, 2016, 32, (4), 1256-1267 View citations (23)
- Identifying Demand Effects in a Large Network of Product Categories
Journal of Retailing, 2016, 92, (1), 25-39 View citations (17)
- The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach
European Journal of Operational Research, 2016, 254, (1), 138-147 View citations (13)
See also Working Paper The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach, Working Papers of Department of Decision Sciences and Information Management, Leuven (2015) (2015)
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