Package: xtcspqardl 1.0.5

xtcspqardl: Cross-Sectionally Augmented Panel Quantile ARDL

Implements the Cross-Sectionally Augmented Panel Quantile Autoregressive Distributed Lag (CS-PQARDL) model and the Quantile Common Correlated Effects Mean Group (QCCEMG) estimator for panel data with cross-sectional dependence. The package handles unobserved common factors through cross-sectional averages following Pesaran (2006) <doi:10.1111/j.1468-0262.2006.00692.x> and Chudik and Pesaran (2015) <doi:10.1016/j.jeconom.2015.03.007>. Quantile regression for dynamic panels follows Harding, Lamarche, and Pesaran (2020) <doi:10.1002/jae.2753>. The ARDL approach to cointegration testing is based on Pesaran, Shin, and Smith (2001) <doi:10.1002/jae.616>.

Authors:Muhammad Alkhalaf [aut, cre, cph]

xtcspqardl_1.0.5.tar.gz
xtcspqardl_1.0.5.zip(r-4.7-any)xtcspqardl_1.0.5.zip(r-4.6-any)xtcspqardl_1.0.5.zip(r-4.5-any)
xtcspqardl_1.0.5.tgz(r-4.6-any)xtcspqardl_1.0.5.tgz(r-4.5-any)
xtcspqardl_1.0.5.tar.gz(r-4.7-any)xtcspqardl_1.0.5.tar.gz(r-4.6-any)
xtcspqardl_1.0.5.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
xtcspqardl/json (API)

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

Bug tracker:https://github.com/muhammedalkhalaf/xtcspqardl/issues

On CRAN:

Conda:

3.40 score 1 stars 365 downloads 2 exports 7 dependencies

Last updated from:ebad877f12. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK112
source / vignettesOK159
linux-releaseOK126
macos-releaseOK105
macos-oldrelOK103
windows-develOK81
windows-releaseOK77
windows-oldrelOK81
wasm-releaseOK73

Exports:compute_csaxtcspqardl

Dependencies:latticeMASSMatrixMatrixModelsquantregSparseMsurvival