sstvars: Toolkit for Reduced Form and Structural Smooth Transition Vector
Autoregressive Models
Penalized and non-penalized 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, counterfactual analysis, and
computation of impulse response functions, generalized impulse response functions,
generalized forecast error variance decompositions, as well as historical
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 (2025) <doi:10.1016/j.jedc.2025.105162>,
Savi Virolainen (2025) <doi:10.48550/arXiv.2404.19707>.
| Version: |
1.2.3 |
| 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: |
2026-01-26 |
| 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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