This package is considered a duplicate. The official version of this package is found at:https://atsa-es.r-universe.dev/varlasso

Package: varlasso 0.0.1

Eric Ward

varlasso: Vector Autoregressive State Space Models With Shrinkage

The varlasso package uses Stan (mc-stan.org) to fit VAR state space models with optional shrinkage priors on B matrix elements (autoregression coefficients).

Authors:Eric Ward [aut, cre], Mark Scheuerell [ctb], Kristin Marshall [ctb]

varlasso_0.0.1.tar.gz
varlasso_0.0.1.zip(r-4.7-x86_64)varlasso_0.0.1.zip(r-4.7-arm64)varlasso_0.0.1.zip(r-4.6-x86_64)varlasso_0.0.1.zip(r-4.6-arm64)varlasso_0.0.1.zip(r-4.5-x86_64)
varlasso_0.0.1.tgz(r-4.6-x86_64)varlasso_0.0.1.tgz(r-4.6-arm64)varlasso_0.0.1.tgz(r-4.5-x86_64)varlasso_0.0.1.tgz(r-4.5-arm64)
varlasso_0.0.1.tar.gz(r-4.7-arm64)varlasso_0.0.1.tar.gz(r-4.7-x86_64)varlasso_0.0.1.tar.gz(r-4.6-arm64)varlasso_0.0.1.tar.gz(r-4.6-x86_64)
varlasso_0.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
varlasso/json (API)

# Install 'varlasso' in R:

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

Bug tracker:https://github.com/nwfsc-timeseries/varlasso/issues

Uses libs:

onetbb– Parallelism library for C++
c++– GNU Standard C++ Library v3

On CRAN:

bayesian multivariate-timeseries time-series onetbb cpp

3.00 score 2 stars 2 scripts 1 exports 49 dependencies

Last updated from:f5d2835faa. Checks:13 NOTE, 2 OK. Indexed: no.

The latest version of this package failed to build. Look at thebuild logs for more information.

Target	Result	Time
linux-devel-arm64	NOTE	309
linux-devel-x86_64	NOTE	356
source / vignettes	OK	348
linux-release-arm64	NOTE	319
linux-release-x86_64	NOTE	364
macos-release-arm64	NOTE	397
macos-release-x86_64	NOTE	512
macos-oldrel-arm64	NOTE	352
macos-oldrel-x86_64	NOTE	580
windows-devel-arm64	NOTE	389
windows-devel-x86_64	NOTE	418
windows-release-arm64	NOTE	388
windows-release-x86_64	NOTE	438
windows-oldrel-x86_64	NOTE	395
wasm-release	OK	204