sstvars: Toolkit for Reduced Form and Structural Smooth Transition Vector
Autoregressive Models
Maximum likelihood estimation of smooth transition vector
autoregressive models with various types of transition weight functions,
conditional distributions, and identification methods. Constrained
estimation with various types of constraints is available. Residual based
model diagnostics, forecasting, simulations, and calculation of impulse
response functions, generalized impulse response functions, and generalized
forecast error variance decompositions. See
Heather Anderson, Farshid Vahid (1998) <doi:10.1016/S0304-4076(97)00076-6>,
Helmut Lütkepohl, Aleksei Netšunajev (2017) <doi:10.1016/j.jedc.2017.09.001>,
Markku Lanne, Savi Virolainen (2024) <doi:10.48550/arXiv.2403.14216>,
Savi Virolainen (2024) <doi:10.48550/arXiv.2404.19707>.
| Version: |
1.1.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Rcpp (≥ 1.0.0), RcppArmadillo (≥ 0.12.0.0.0), parallel (≥
4.0.0), pbapply (≥ 1.7-0), stats (≥ 4.0.0), graphics (≥
4.0.0), utils (≥ 4.0.0) |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
knitr, rmarkdown |
| Published: |
2024-12-07 |
| DOI: |
10.32614/CRAN.package.sstvars |
| Author: |
Savi Virolainen 
[aut, cre] |
| Maintainer: |
Savi Virolainen <savi.virolainen at helsinki.fi> |
| BugReports: |
https://github.com/saviviro/sstvars/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/saviviro/sstvars |
| NeedsCompilation: |
yes |
| SystemRequirements: |
BLAS, LAPACK |
| Materials: |
README NEWS |
| In views: |
Econometrics, TimeSeries |
| CRAN checks: |
sstvars results |
Documentation:
Downloads:
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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.