Software
Time Series Analysis:
TCA: Julia and Matlab code, developed by Enrico Wegner, on transmission channel analysis in dynamic models
RR-MAR: Julia code, developed by Ivan Ricardo, on reduced-rank matrix-autoregressive models
ml-crosstemporal-reconciliation: R code, developed by Marie Ternes, on cross-temporal forecast reconciliation through machine learning
HDLP: R code, developed by Robert Adamek, for local projection inference in high-dimensions
changepoint.influence: R code, developed by Rebecca Killick and Ines Wilms, to calculate the influence of the data on a changepoint segmentation
hierarchical-MFVAR: R code, developed by Marie Ternes, on hierarchical regularizers for mixed-frequency vector autoregressions.
desla: R package, developed by Robert Adamek, for inference in high-dimensional time series models via the desparsified lasso.
bootUR: R package, developed by Stephan Smeekes and Ines Wilms, for bootstrap unit root testing. userguide
bigtime: R package, developed by Ines Wilms, David S. Matteson, Jacob Bien, Sumanta Basu, Will Nicholson and Enrico Wegner, for sparse estimation of large Vector AutoRegressive (VAR) Models, Vector AutoRegressive with Exogenous Variables X (VARX) Models and VectorAutoRegressive Moving Average (VARMA) Models: userguide
Sparse estimation of the Vector AutoRegressive Model: Code, Example.
Sparse estimation of the Multi-class Vector AutoRegressive Model: Code.
Sparse cointegration: Code.
Graphical Modeling:
CGGMR:: R code, developed by Daniël Touw, on the clusterpath estimator of Gaussian graphical models
taglasso: Tree-based node aggregation in sparse graphical models.
Principal Component Analysis:
ssMRCD: R code, developed by Patricia Puchhammer on sparse robust PCA for multi-source data
Canonical Correlation Analysis:
Discriminant Analysis:
Cellwise robust regularized Discriminant Analysis: Code.