Package: starvars
Type: Package
Title: Vector Logistic Smooth Transition Models Estimation and
        Prediction
Version: 1.1.10
Authors@R: c(
  person("Andrea", "Bucci", email = "andrea.bucci@unich.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: 7.1.1
Config/pak/sysreqs: cmake libfontconfig1-dev libfreetype6-dev
        libfribidi-dev make libharfbuzz-dev libicu-dev libjpeg-dev
        libpng-dev libuv1-dev libxml2-dev libssl-dev zlib1g-dev
Repository: https://andbucci.r-universe.dev
Date/Publication: 2022-01-17 17:03:29 UTC
RemoteUrl: https://github.com/andbucci/starvars
RemoteRef: HEAD
RemoteSha: c4b8fcb3bc06718f1109699bfbf2c408ff0617c0
NeedsCompilation: no
Packaged: 2026-06-19 10:22:17 UTC; root
Author: Andrea Bucci [aut, cre, cph],
  Giulio Palomba [aut],
  Eduardo Rossi [aut],
  Andrea Faragalli [ctb]
Maintainer: Andrea Bucci <andrea.bucci@unich.it>