sparseVAR, sparseVARMA,
sparseVARX are all more efficient and faster nowfitted and residuals functions were
implemented for VAR, VARMA, VARXdiagnostics_plot was implemented for VAR, VARMA,
VARXplot_cv was implemented; Allows to investigate the
behavior in CVsparseVAR, sparseVARMA and
sparseVARX can now use information criteria to select the
optimal penalizationsimVAR allow for the simulation of VAR models using
different sparsity patterns; utility functions summary and
plot were also implemented for simulated VARssparseVAR,
sparseVARMA and sparseVARX changed to “none”.
Will return a 3D array of estimations from this version on, unless a
different selection procedure is chosen. WARNING: This can break
old code!recursiveforecast was implemented for VAR models.is.stable was implemented for VAR modelsplot_cv, directforecast, and
lagmatrix the model argument was removed. Functions know
automatically what model was used. WARNING: This can break old
code!
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