8 citations · 19 across the 15 of their papers we have counts for
6 papers · 1 filter
An algorithm for the multivariate group lasso with covariance estimation
Ines Wilms, Christophe Croux
We study a group lasso estimator for the multivariate linear regression model that accounts for correlated error terms. A block coordinate descent algorithm is used to compute this…
The predictive power of the business and bank sentiment of firms: A high-dimensional Granger Causality approach
Ines Wilms, Sarah Gelper, Christophe Croux
We study the predictive power of industry-specific economic sentiment indicators for future macro-economic developments. In addition to the sentiment of firms towards their own bus…
Identifying Demand Effects in a Large Network of Product Categories
Sarah Gelper, Ines Wilms, Christophe Croux
Planning marketing mix strategies requires retailers to understand within- as well as cross-category demand effects. Most retailers carry products in a large variety of categories,…
Sparse cointegration
Ines Wilms, Christophe Croux
Cointegration analysis is used to estimate the long-run equilibrium relations between several time series. The coefficients of these long-run equilibrium relations are the cointegr…
Robust Sparse Canonical Correlation Analysis
Ines Wilms, Christophe Croux
Canonical correlation analysis (CCA) is a multivariate statistical method which describes the associations between two sets of variables. The objective is to find linear combinatio…
Sparse canonical correlation analysis from a predictive point of view
Ines Wilms, Christophe Croux
Canonical correlation analysis (CCA) describes the associations between two sets of variables by maximizing the correlation between linear combinations of the variables in each dat…