DWaveNARDL: Dual Wavelet Based NARDL Model

Dual Wavelet based Nonlinear Autoregressive Distributed Lag model has been developed for noisy time series analysis. This package is designed to capture both short-run and long-run relationships in time series data, while incorporating wavelet transformations. The methodology combines the NARDL model with wavelet decomposition to better capture the nonlinear dynamics of the series and exogenous variables. The package is useful for analyzing economic and financial time series data that exhibit both long-term trends and short-term fluctuations. This package has been developed using algorithm of Jammazi et al. <doi:10.1016/j.intfin.2014.11.011>.

Version:	0.1.0
Imports:	nardl, wavelets, stats, roxygen2
Published:	2025-04-30
DOI:	10.32614/CRAN.package.DWaveNARDL
Author:	Md Yeasin [aut, cre], Ranjit Kumar Paul [aut], Ranjit Kumar Upadhyay [aut], Anita Sarkar [aut], Amrit Kumar Paul [aut]
Maintainer:	Md Yeasin <yeasin.iasri at gmail.com>
License:	GPL-3
NeedsCompilation:	no
CRAN checks:	DWaveNARDL results

Documentation:

Reference manual:

DWaveNARDL.pdf

Downloads:

Package source:	DWaveNARDL_0.1.0.tar.gz
Windows binaries:	r-devel: DWaveNARDL_0.1.0.zip, r-release: DWaveNARDL_0.1.0.zip, r-oldrel: DWaveNARDL_0.1.0.zip
macOS binaries:	r-release (arm64): DWaveNARDL_0.1.0.tgz, r-oldrel (arm64): DWaveNARDL_0.1.0.tgz, r-release (x86_64): DWaveNARDL_0.1.0.tgz, r-oldrel (x86_64): DWaveNARDL_0.1.0.tgz

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