Package: DREGAR 0.1.3.0

DREGAR: Regularized Estimation of Dynamic Linear Regression in the Presence of Autocorrelated Residuals (DREGAR)

A penalized/non-penalized implementation for dynamic regression in the presence of autocorrelated residuals (DREGAR) using iterative penalized/ordinary least squares. It applies Mallows CP, AIC, BIC and GCV to select the tuning parameters.

Authors:Hamed Haselimashhadi

DREGAR_0.1.3.0.tar.gz
DREGAR_0.1.3.0.zip(r-4.5)DREGAR_0.1.3.0.zip(r-4.4)DREGAR_0.1.3.0.zip(r-4.3)
DREGAR_0.1.3.0.tgz(r-4.4-any)DREGAR_0.1.3.0.tgz(r-4.3-any)
DREGAR_0.1.3.0.tar.gz(r-4.5-noble)DREGAR_0.1.3.0.tar.gz(r-4.4-noble)
DREGAR_0.1.3.0.tgz(r-4.4-emscripten)DREGAR_0.1.3.0.tgz(r-4.3-emscripten)
DREGAR.pdf |DREGAR.html
DREGAR/json (API)

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

Peer review:

On CRAN:

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 5 scripts 477 downloads 4 exports 1 dependencies

Last updated 8 years agofrom:d96d583ca4. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 01 2024
R-4.5-winOKNov 01 2024
R-4.5-linuxOKNov 01 2024
R-4.4-winOKNov 01 2024
R-4.4-macOKNov 01 2024
R-4.3-winOKNov 01 2024
R-4.3-macOKNov 01 2024

Exports:dregar2dregar6generateARsim.dregar

Dependencies:msgps