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starvars  

Vector Logistic Smooth Transition Models Estimation and Prediction
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("starvars", "1.1.10")



Attach the package and use:
library("starvars")
Maintained by
Andrea Bucci
[Scholar Profile | Author Map]
First Published: 2020-05-04
Latest Update: 2022-01-17
Description:
Allows the user to estimate a vector logistic smooth transition autoregressive model via maximum log-likelihood or nonlinear least squares. It further permits to test for linearity in the multivariate framework against a vector logistic smooth transition autoregressive model with a single transition variable. The estimation method is discussed in Terasvirta and Yang (2014, <doi:10.1108/S0731-9053(2013)0000031008>). Also, realized covariances can be constructed from stock market prices or returns, as explained in Andersen et al. (2001, <doi:10.1016/S0304-405X(01)00055-1>).
How to cite:
Andrea Bucci (2020). starvars: Vector Logistic Smooth Transition Models Estimation and Prediction. R package version 1.1.10, https://cran.r-project.org/web/packages/starvars. Accessed 28 Feb. 2025.
Previous versions and publish date:
0.1.7 (2020-05-04 16:40), 0.1.8 (2020-08-13 12:00), 1.1.1 (2020-09-17 13:50), 1.1.2 (2021-01-11 12:20), 1.1.5 (2021-09-13 17:30), 1.1.7 (2021-09-17 13:00), 1.1.8 (2021-10-29 10:30), 1.1.9 (2021-11-01 17:00)
Other packages that cited starvars R package
View starvars citation profile
Other R packages that starvars depends, imports, suggests or enhances
Complete documentation for starvars
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