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Details about Ines Wilms

Homepage:https://www.maastrichtuniversity.nl/i.wilms
Workplace:Vakgroep Kwantitatieve Economie (Department of Quantitative Economics), School of Business and Economics, Maastricht University, (more information at EDIRC)

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

  1. Cross-Temporal Forecast Reconciliation at Digital Platforms with Machine Learning
    Papers, arXiv.org Downloads
  2. Fast Forecasting of Unstable Data Streams for On-Demand Service Platforms
    Papers, arXiv.org Downloads
  3. Hierarchical Regularizers for Reverse Unrestricted Mixed Data Sampling Regressions
    Papers, arXiv.org Downloads View citations (1)
  4. Local Projection Inference in High Dimensions
    Papers, arXiv.org Downloads
    See also Journal Article Local projection inference in high dimensions, The Econometrics Journal, Royal Economic Society (2024) Downloads (2024)
  5. Reduced-Rank Matrix Autoregressive Models: A Medium $N$ Approach
    Papers, arXiv.org Downloads
  6. Transmission Channel Analysis in Dynamic Models
    Papers, arXiv.org Downloads
  7. Vector AutoRegressive Moving Average Models: A Review
    Papers, arXiv.org Downloads

2023

  1. Sparse High-Dimensional Vector Autoregressive Bootstrap
    Papers, arXiv.org Downloads

2022

  1. Detecting Anti-dumping Circumvention: A Network Approach
    Papers, arXiv.org Downloads
  2. Hierarchical Regularizers for Mixed-Frequency Vector Autoregressions
    Papers, arXiv.org Downloads View citations (2)
  3. Lasso Inference for High-Dimensional Time Series
    Papers, arXiv.org Downloads View citations (4)
    See also Journal Article Lasso inference for high-dimensional time series, Journal of Econometrics, Elsevier (2023) Downloads View citations (6) (2023)
  4. bootUR: An R Package for Bootstrap Unit Root Tests
    Papers, arXiv.org Downloads View citations (1)

2021

  1. Tree-based Node Aggregation in Sparse Graphical Models
    Papers, arXiv.org Downloads

2018

  1. White heteroscedasticty testing after outlier removal
    Economics Series Working Papers, University of Oxford, Department of Economics Downloads View citations (5)

2017

  1. 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 Downloads
  2. Volatility Spillovers and Heavy Tails: A Large t-Vector AutoRegressive Approach
    Papers, arXiv.org Downloads
    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) Downloads View citations (1)

2016

  1. Commodity Dynamics: A Sparse Multi-class Approach
    Papers, arXiv.org Downloads 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) Downloads

    See also Journal Article Commodity dynamics: A sparse multi-class approach, Energy Economics, Elsevier (2016) Downloads View citations (8) (2016)
  2. 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 Downloads
  3. 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 Downloads
    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) Downloads View citations (1) (2018)

2015

  1. 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 Downloads
    See also Journal Article An algorithm for the multivariate group lasso with covariance estimation, Journal of Applied Statistics, Taylor & Francis Journals (2018) Downloads View citations (3) (2018)
  2. 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 Downloads
    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) Downloads View citations (13) (2016)

2014

  1. 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 Downloads

Journal Articles

2024

  1. Local projection inference in high dimensions
    The Econometrics Journal, 2024, 27, (3), 323-342 Downloads
    See also Working Paper Local Projection Inference in High Dimensions, Papers (2024) Downloads (2024)

2023

  1. Lasso inference for high-dimensional time series
    Journal of Econometrics, 2023, 235, (2), 1114-1143 Downloads View citations (6)
    See also Working Paper Lasso Inference for High-Dimensional Time Series, Papers (2022) Downloads View citations (4) (2022)
  2. Sparse Identification and Estimation of Large-Scale Vector AutoRegressive Moving Averages
    Journal of the American Statistical Association, 2023, 118, (541), 571-582 Downloads View citations (1)

2022

  1. Sparse regression for large data sets with outliers
    European Journal of Operational Research, 2022, 297, (2), 782-794 Downloads View citations (7)

2021

  1. Heteroscedasticity testing after outlier removal
    Econometric Reviews, 2021, 40, (1), 51-85 Downloads View citations (1)
  2. Multivariate volatility forecasts for stock market indices
    International Journal of Forecasting, 2021, 37, (2), 484-499 Downloads View citations (19)

2020

  1. Volatility spillovers in commodity markets: A large t-vector autoregressive approach
    Energy Economics, 2020, 85, (C) Downloads View citations (40)

2018

  1. An algorithm for the multivariate group lasso with covariance estimation
    Journal of Applied Statistics, 2018, 45, (4), 668-681 Downloads 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) Downloads (2015)
  2. Multiclass vector auto‐regressive models for multistore sales data
    Journal of the Royal Statistical Society Series C, 2018, 67, (2), 435-452 Downloads 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) Downloads (2016)

2016

  1. Commodity dynamics: A sparse multi-class approach
    Energy Economics, 2016, 60, (C), 62-72 Downloads View citations (8)
    See also Working Paper Commodity Dynamics: A Sparse Multi-class Approach, Papers (2016) Downloads View citations (8) (2016)
  2. Discussion of ‘Asymptotic Theory of Outlier Detection Algorithms for Linear Time Series Regression Models’
    Scandinavian Journal of Statistics, 2016, 43, (2), 353-356 Downloads
  3. Forecasting using sparse cointegration
    International Journal of Forecasting, 2016, 32, (4), 1256-1267 Downloads View citations (23)
  4. Identifying Demand Effects in a Large Network of Product Categories
    Journal of Retailing, 2016, 92, (1), 25-39 Downloads View citations (17)
  5. 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 Downloads 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) Downloads (2015)
 
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