Package: micvar 0.1.0

micvar: Order Selection in Vector Autoregression by Mean Square Information Criteria

Implements order selection for Vector Autoregressive (VAR) models using the Mean Square Information Criterion (MIC). Unlike standard methods such as AIC and BIC, MIC is likelihood-free. This method consistently estimates VAR order and has robust performance under model misspecification. For more details, see Hellstern and Shojaie (2025) <doi:10.48550/arXiv.2511.19761>.

Authors:Michael Hellstern [aut, cre]

micvar_0.1.0.tar.gz
micvar_0.1.0.zip(r-4.7-any)micvar_0.1.0.zip(r-4.6-any)micvar_0.1.0.zip(r-4.5-any)
micvar_0.1.0.tgz(r-4.6-any)micvar_0.1.0.tgz(r-4.5-any)
micvar_0.1.0.tar.gz(r-4.7-any)micvar_0.1.0.tar.gz(r-4.6-any)
micvar_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
micvar/json (API)

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 1 stars 168 downloads 4 exports 4 dependencies

Last updated from:04d5026410. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK78
source / vignettesOK129
linux-releaseOK90
macos-releaseOK164
macos-oldrelOK196
windows-develOK57
windows-releaseOK76
windows-oldrelOK57
wasm-releaseOK72

Exports:gen_coef_matmicvarsim_varverify_stability

Dependencies:MASSmatrixcalcrbibutilsRdpack