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starvars

Vector Logistic Smooth Transition Models Estimation and Prediction

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>).

Versions across snapshots

VersionRepositoryFileSize
1.1.11 rolling linux/jammy R-4.5 starvars_1.1.11.tar.gz 363.9 KiB
1.1.11 rolling linux/noble R-4.5 starvars_1.1.11.tar.gz 363.9 KiB
1.1.11 rolling source/ R- starvars_1.1.11.tar.gz 246.2 KiB
1.1.11 latest linux/jammy R-4.5 starvars_1.1.11.tar.gz 363.9 KiB
1.1.11 latest linux/noble R-4.5 starvars_1.1.11.tar.gz 363.9 KiB
1.1.11 latest source/ R- starvars_1.1.11.tar.gz 246.2 KiB
1.1.11 2026-04-26 source/ R- starvars_1.1.11.tar.gz 246.2 KiB
1.1.11 2026-04-23 source/ R- starvars_1.1.11.tar.gz 246.2 KiB
1.1.11 2026-04-09 windows/windows R-4.5 starvars_1.1.11.zip 366.9 KiB
1.1.10 2025-04-20 source/ R- starvars_1.1.10.tar.gz 245.8 KiB

Dependencies (latest)

Imports