Package: bayesDccGarch 3.0.4

bayesDccGarch: Methods and Tools for Bayesian Dynamic Conditional Correlation GARCH(1,1) Model

Bayesian estimation of dynamic conditional correlation GARCH model for multivariate time series volatility (Fioruci, J.A., Ehlers, R.S. and Andrade-Filho, M.G., (2014). <doi:10.1080/02664763.2013.839635>.

Authors:Jose Augusto Fiorucci [aut, cre, cph], Ricardo Sanders Ehlers [aut, cph], Francisco Louzada [aut, cph]

bayesDccGarch_3.0.4.tar.gz
bayesDccGarch_3.0.4.zip(r-4.7)bayesDccGarch_3.0.4.zip(r-4.6)bayesDccGarch_3.0.4.zip(r-4.5)
bayesDccGarch_3.0.4.tgz(r-4.6-x86_64)bayesDccGarch_3.0.4.tgz(r-4.6-arm64)bayesDccGarch_3.0.4.tgz(r-4.5-x86_64)bayesDccGarch_3.0.4.tgz(r-4.5-arm64)
bayesDccGarch_3.0.4.tar.gz(r-4.7-arm64)bayesDccGarch_3.0.4.tar.gz(r-4.7-x86_64)bayesDccGarch_3.0.4.tar.gz(r-4.6-arm64)bayesDccGarch_3.0.4.tar.gz(r-4.6-x86_64)
bayesDccGarch_3.0.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
bayesDccGarch/json (API)

# Install 'bayesDccGarch' in R:

install.packages('bayesDccGarch', repos = c('https://jafiorucci.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/jafiorucci/bayesdccgarch/issues

Datasets:

DaxCacNik - Log-returns of daily indices of stock markets in Frankfurt, Paris and Tokio

On CRAN:

2.70 score 1 stars 6 scripts 302 downloads 10 exports 3 dependencies

Last updated from:a554c59855. Checks:11 NOTE, 2 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	NOTE	95
linux-devel-x86_64	NOTE	99
source / vignettes	OK	154
linux-release-arm64	NOTE	92
linux-release-x86_64	NOTE	95
macos-release-arm64	NOTE	122
macos-release-x86_64	NOTE	171
macos-oldrel-arm64	NOTE	80
macos-oldrel-x86_64	NOTE	254
windows-devel	NOTE	64
windows-release	NOTE	73
windows-oldrel	NOTE	74
wasm-release	OK	89

Exports:bayesDccGarch dssged dssnorm dsst increaseSim logLikDccGarch plot.bayesDccGarch plotVol predict.bayesDccGarch update.bayesDccGarch

Dependencies:coda lattice numDeriv

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
bayesDccGARCH: Methods and tools for Bayesian analysis of DCC-GARCH(1,1) Model.	bayesDccGarch-package
Bayesian Estimation of the DCC-GARCH(1,1) Model.	bayesDccGarch increaseSim update update.bayesDccGarch window window.bayesDccGarch
Log-returns of daily indices of stock markets in Frankfurt, Paris and Tokio	DaxCacNik
Density functions of multivariate Standard Skew Norm, t-Student and GED distributions	dssged dssnorm dsst
The logarithm of likelihood function of DCC-GARCH(1,1) Model.	logLikDccGarch
Plotting volatilities for Bayesian DCC-GARCH model	plot plot.bayesDccGarch
Plotting volatilities of time series	plotVol
Bayesian forecast for volatilities and coditional correlations	predict predict.bayesDccGarch