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>).
| Version: | 1.1.2 |
| Depends: | R (≥ 4.0) |
| Imports: | MASS, ks, zoo, data.table, dplyr, methods, matrixcalc, vars, maxLik, rlist, fGarch, lubridate, xts, lessR, quantmod |
| Published: | 2021-01-11 |
| Author: | Andrea Bucci [aut, cre, cph], Giulio Palomba [aut], Eduardo Rossi [aut], Andrea Faragalli [ctb] |
| Maintainer: | Andrea Bucci <andrea.bucci at unich.it> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| URL: | https://github.com/andbucci/starvars |
| NeedsCompilation: | no |
| Materials: | README |
| CRAN checks: | starvars results |
| Reference manual: | starvars.pdf |
| Package source: | starvars_1.1.2.tar.gz |
| Windows binaries: | r-devel: starvars_1.1.2.zip, r-release: starvars_1.1.2.zip, r-oldrel: starvars_1.1.1.zip |
| macOS binaries: | r-release: starvars_1.1.2.tgz, r-oldrel: starvars_1.1.1.tgz |
| Old sources: | starvars archive |
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