postshock: Donor-Adjusted Post-Shock Forecasting

Implements donor-adjusted methods for forecasting conditional means and variances after structural shocks. Historical donor episodes are weighted using covariates observed before each shock, and their estimated post-shock effects are combined with forecasts from a target-series model. The methods build on Lin and Eck (2021) <doi:10.1016/j.ijforecast.2021.03.010>. The package supports donor balancing weights, structured donor pools, autoregressive integrated moving average models, and generalized autoregressive conditional heteroscedasticity models with external regressors.

Version:	0.2.0
Depends:	R (≥ 4.1.0)
Imports:	Rsolnp, garchx, forecast, lmtest, xts, zoo
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2026-07-27
DOI:	10.32614/CRAN.package.postshock
Author:	Qiyang Wang [aut, cre], Daniel J. Eck [aut]
Maintainer:	Qiyang Wang <wangqiyang497 at gmail.com>
License:	MIT + file LICENSE
NeedsCompilation:	no
Language:	en-US
Materials:	README
CRAN checks:	postshock results

Documentation:

Reference manual:	postshock.html , postshock.pdf
Vignettes:	Post-Shock Forecasting Workflow (source, R code)

Downloads:

Package source:	postshock_0.2.0.tar.gz
Windows binaries:	r-devel: postshock_0.2.0.zip, r-release: postshock_0.2.0.zip, r-oldrel: postshock_0.2.0.zip
macOS binaries:	r-release (arm64): postshock_0.2.0.tgz, r-oldrel (arm64): postshock_0.2.0.tgz, r-release (x86_64): postshock_0.2.0.tgz, r-oldrel (x86_64): postshock_0.2.0.tgz

Linking:

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