Package: starvars
Type: Package
Title: Vector Logistic Smooth Transition Models Estimation and
        Prediction
Version: 1.1.11
Authors@R: c(
  person("Andrea", "Bucci", email = "andrea.bucci@unimc.it", role = c("aut", "cre", "cph")),
  person("Giulio", "Palomba", role = "aut"),
  person("Eduardo", "Rossi", role = "aut"),
  person("Andrea", "Faragalli", role = "ctb")
  )
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>).
License: GPL
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: MASS, ks, zoo, doSNOW, foreach, methods, matrixcalc,
        optimParallel, parallel, vars, xts, lessR, quantmod
URL: https://github.com/andbucci/starvars
RoxygenNote: 7.3.3
NeedsCompilation: no
Packaged: 2026-01-26 15:48:35 UTC; andre
Author: Andrea Bucci [aut, cre, cph],
  Giulio Palomba [aut],
  Eduardo Rossi [aut],
  Andrea Faragalli [ctb]
Maintainer: Andrea Bucci <andrea.bucci@unimc.it>
Repository: CRAN
Date/Publication: 2026-01-26 17:10:01 UTC
Built: R 4.6.0; ; 2026-04-30 17:14:45 UTC; unix
