| sstvars-package {sstvars} | R Documentation |
sstvars: toolkit for reduced form and structural smooth transition vector autoregressive models
Description
sstvars is a package for reduced form and structural smooth transition vector
autoregressive models. The package implements various transition weight functions, conditional distributions,
identification methods, and parameter restrictions. The model parameters are estimated with the method of maximum
likelihood by running multiple rounds of a two-phase estimation procedure in which a genetic algorithm is used
to find starting values for a gradient based method. For evaluating the adequacy of the estimated models,
sstvars utilizes residuals based diagnostics and provides functions for graphical diagnostics and for calculating
formal diagnostic tests. sstvars also accommodates the estimation of linear impulse response functions, nonlinear
generalized impulse response functions, and generalized forecast error variance decompositions. Further functionality includes
hypothesis testing, plotting the profile log-likelihood functions about the estimate, simulation from STVAR processes,
and forecasting, for example.
The vignette is a good place to start, and see also the readme file.
Author(s)
you <savi.virolainen@helsinki.fi>
See Also
Useful links: