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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).
- Version1.1.10
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release01/17/2022
Documentation
Team
Andrea Bucci
Giulio Palomba
Show author detailsRolesAuthorEduardo Rossi
Show author detailsRolesAuthorAndrea Faragalli
Show author detailsRolesContributor
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- Imports11 packages