Package: svars
Type: Package
Title: Data-Driven Identification of SVAR Models
Version: 1.3.3
Date: 2020-01-07
Author: Alexander Lange [aut, cre],
  Bernhard Dalheimer [aut],
  Helmut Herwartz [aut],
  Simone Maxand [aut],
  Hannes Riebl [ctb]
Authors@R: c(person("Alexander", "Lange", role = c("aut", "cre"), email = "alexander.lange@uni-goettingen.de"), person("Bernhard", "Dalheimer", role = c("aut"), email = "bernhard.dalheimer@uni-goettingen.de"), person("Helmut", "Herwartz", role = c("aut"), email = "hherwartz@uni-goettingen.de"), person("Simone", "Maxand", role = c("aut"), email = "smaxand@uni-goettingen.de"), person("Hannes", "Riebl", role = c("ctb")))
Maintainer: Alexander Lange <alexander.lange@uni-goettingen.de>
Description: Implements data-driven identification methods for structural vector autoregressive (SVAR) models. 
             Based on an existing VAR model object (provided by e.g. VAR() from the 'vars' package), the structural 
             impact matrix is obtained via data-driven identification techniques (i.e. changes in volatility (Rigobon, R. (2003) <doi:10.1162/003465303772815727>),  patterns of GARCH (Normadin, M., Phaneuf, L. (2004) <doi:10.1016/j.jmoneco.2003.11.002>),
             independent component analysis (Matteson, D. S, Tsay, R. S., (2013) <doi:10.1080/01621459.2016.1150851>), least dependent innovations (Herwartz, H., Ploedt, M., (2016) <doi:10.1016/j.jimonfin.2015.11.001>), 
             smooth transition in variances (Luetkepohl, H., Netsunajev, A. (2017) <doi:10.1016/j.jedc.2017.09.001>) or non-Gaussian maximum likelihood (Lanne, M., Meitz, M., Saikkonen, P. (2017) <doi:10.1016/j.jeconom.2016.06.002>)).
Depends: R (>= 2.10), vars (>= 1.5.3)
Imports: expm, reshape2, ggplot2, copula, clue, pbapply, steadyICA,
        DEoptim, zoo, strucchange, Rcpp
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
License: MIT + file LICENSE
LazyData: TRUE
RoxygenNote: 7.0.2
Suggests: testthat (>= 2.1.0), knitr, rmarkdown, tsDyn
VignetteBuilder: knitr
Packaged: 2020-01-08 13:09:29 UTC; alex
Repository: CRAN
Date/Publication: 2020-01-09 18:50:03 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 08:26:32 UTC; windows
Archs: i386, x64
