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]

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bayesDccGarch.pdf |bayesDccGarch.html✨
bayesDccGarch/json (API)

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

Peer review:

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 354 downloads 10 exports 3 dependencies

Last updated 2 years agofrom:a554c59855. Checks:OK: 4 NOTE: 5. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 07 2024
R-4.5-win-x86_64NOTENov 07 2024
R-4.5-linux-x86_64NOTENov 07 2024
R-4.4-win-x86_64NOTENov 07 2024
R-4.4-mac-x86_64NOTENov 07 2024
R-4.4-mac-aarch64NOTENov 07 2024
R-4.3-win-x86_64OKNov 07 2024
R-4.3-mac-x86_64OKNov 07 2024
R-4.3-mac-aarch64OKNov 07 2024

Exports:bayesDccGarchdssgeddssnormdsstincreaseSimlogLikDccGarchplot.bayesDccGarchplotVolpredict.bayesDccGarchupdate.bayesDccGarch

Dependencies:codalatticenumDeriv