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sstvars  

Toolkit for Reduced Form and Structural Smooth Transition Vector Autoregressive Models
View on CRAN: Click here


Download and install sstvars package within the R console
Install from CRAN:
install.packages("sstvars")

Install from Github:
library("remotes")
install_github("cran/sstvars")

Install by package version:
library("remotes")
install_version("sstvars", "1.1.4")



Attach the package and use:
library("sstvars")
Maintained by
Savi Virolainen
[Scholar Profile | Author Map]
First Published: 2024-05-27
Latest Update: 2024-05-29
Description:
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>.
How to cite:
Savi Virolainen (2024). sstvars: Toolkit for Reduced Form and Structural Smooth Transition Vector Autoregressive Models. R package version 1.1.4, https://cran.r-project.org/web/packages/sstvars. Accessed 06 Apr. 2025.
Previous versions and publish date:
1.0.0 (2024-05-27 19:50), 1.0.1 (2024-05-29 08:50), 1.1.0 (2024-11-29 16:40), 1.1.1 (2024-12-07 14:30), 1.1.2 (2025-01-08 06:00), 1.1.3 (2025-01-30 13:00), 1.1.4 (2025-02-27 16:20)
Other packages that cited sstvars R package
View sstvars citation profile
Other R packages that sstvars depends, imports, suggests or enhances
Complete documentation for sstvars
Functions, R codes and Examples using the sstvars R package
Full sstvars package functions and examples
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