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NEW!!! rpkg.net flagship R package "quickcode" now available in CRAN quickcode TM
sstvars
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", "1.0.1")
Attach the package and use:
library("sstvars")
Maintained by
Savi Virolainen
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
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 1.0.1, https://cran.r-project.org/web/packages/sstvars
Previous versions and publish date:
1.0.0 (2024-05-27 19:50)
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