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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!These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.