Vector Logistic Smooth Transition Models / Realized Covariances Construction

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, ). Also, realized covariances can be constructed from stock market prices or returns, as explained in Andersen et al. (2001, ).


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install.packages("starvars")

1.1.1 by Andrea Bucci, a month ago


https://github.com/andbucci/starvars


Browse source code at https://github.com/cran/starvars


Authors: Andrea Bucci [aut, cre, cph] , Giulio Palomba [aut] , Eduardo Rossi [aut] , Andrea Faragalli [ctb]


Documentation:   PDF Manual  


GPL license


Imports MASS, ks, zoo, data.table, methods, matrixcalc, vars, maxLik, rlist, fGarch, lubridate, xts, lessR, quantmod


See at CRAN