Description: Time series regression using dynamic linear models fit using
MCMC. See Scott and Varian (2014) <DOI:10.1504/IJMMNO.2014.059942>, among many
Depends: BoomSpikeSlab (>= 0.9.0), zoo, xts, Boom (>= 0.7), R(>= 3.3.1)
Packaged: 2017-05-25 17:01:34 UTC; stevescott

Depends: BoomSpikeSlab (>= 1.0.0), zoo, xts, Boom (>= 0.8), R(>= 3.3.1)
Packaged: 2018-05-06 14:26:29 UTC; stevescott

Depends: BoomSpikeSlab (>= 1.1.0), zoo, xts, Boom (>= 0.9), R(>= 3.4.0)
Packaged: 2019-05-21 17:07:09 UTC; stevescott

Depends: BoomSpikeSlab (>= 1.1.1), zoo, xts, Boom (>= 0.9.1), R(>=
Packaged: 2019-06-04 01:04:56 UTC; stevescott

Depends: BoomSpikeSlab (>= 1.2.1), zoo, xts, Boom (>= 0.9.2), R(>=
Packaged: 2019-09-04 15:04:45 UTC; stevescott

Depends: BoomSpikeSlab (>= 1.2.3), zoo (>= 1.8), xts, Boom (>= 0.9.6),

Depends: BoomSpikeSlab (>= 1.2.4), zoo (>= 1.8), xts, Boom (>= 0.9.7),

Title: Submitter and Monitor of the 'LSF Cluster'
Imports: GlobalOptions (>= 0.1.1), GetoptLong (>= 0.1.8), digest,
utils, stats, clisymbols, crayon, methods, grDevices, graphics
Suggests: knitr, ssh, DT (>= 0.13), shiny (>= 1.0.0), shinyjqui,
Description: It submits R code/R scripts/shell commands to 'LSF cluster'
(<https://en.wikipedia.org/wiki/Platform_LSF>, the 'bsub' system) without
leaving R. There is also an interactive 'shiny' app for monitoring the job status.

igraph, graph, Rgraphviz, ggplot2, markdown

igraph, graph, Rgraphviz, ggplot2, rmarkdown, markdown

Title: Bayesian Estimation of Structural Vector Autoregressive Models
Authors@R: person("Tomasz", "Woźniak", , "wozniak.tom@pm.me", role = c("aut", "cre"),
Description: Efficient algorithms for Bayesian estimation of Structural Vector Autoregressive (SVAR) models via Markov chain Monte Carlo methods. A wide range of SVAR models is considered, including homo- and heteroskedastic specifications and those with non-normal structural shocks. The heteroskedastic SVAR model setup is similar as in Woźniak & Droumaguet (2015) <doi:10.13140/RG.2.2.19492.55687> and Lütkepohl & Woźniak (2020) <doi:10.1016/j.jedc.2020.103862>. The sampler of the structural matrix follows Waggoner & Zha (2003) <doi:10.1016/S0165-1889(02)00168-9>, whereas that for autoregressive parameters follows Chan, Koop, Yu (2022) <https://www.joshuachan.org/papers/OISV.pdf>. The specification of Markov switching heteroskedasticity is inspired by Song & Woźniak (2021) <doi:10.1093/acrefore/9780190625979.013.174>, and that of Stochastic Volatility model by Kastner & Frühwirth-Schnatter (2014) <doi:10.1016/j.csda.2013.01.002>.
Imports: Rcpp (>= 1.0.7), RcppProgress (>= 0.1), RcppTN, GIGrvg, R6
LinkingTo: Rcpp, RcppProgress, RcppArmadillo, RcppTN
Author: Tomasz Woźniak [aut, cre] (<https://orcid.org/0000-0003-2212-2378>)