dLagM: Time Series Regression Models with Distributed Lag Models

Provides time series regression models with one predictor using finite distributed lag models, polynomial (Almon) distributed lag models, geometric distributed lag models with Koyck transformation, and autoregressive distributed lag models. It also consists of functions for computation of h-step ahead forecasts from these models. See Baltagi (2011) <doi:10.1007/978-3-642-20059-5> for more information.

Version: 1.0.19
Depends: graphics, stats, nardl, dynlm, R (≥ 3.5.0)
Imports: AER, formula.tools, plyr , lmtest, strucchange, wavethresh, MASS, roll
Published: 2019-10-23
Author: Haydar Demirhan [aut, cre, cph] (<https://orcid.org/0000-0002-8565-4710>)
Maintainer: Haydar Demirhan <haydar.demirhan at rmit.edu.au>
License: GPL-3
NeedsCompilation: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: dLagM results


Reference manual: dLagM.pdf
Package source: dLagM_1.0.19.tar.gz
Windows binaries: r-devel: dLagM_1.0.19.zip, r-devel-gcc8: dLagM_1.0.19.zip, r-release: dLagM_1.0.19.zip, r-oldrel: dLagM_1.0.19.zip
OS X binaries: r-release: dLagM_1.0.19.tgz, r-oldrel: dLagM_1.0.19.tgz
Old sources: dLagM archive


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