MultiGrey: Fitting and Forecasting of Grey Model for Multivariate Time Series Data

Grey model is commonly used in time series forecasting when statistical assumptions are violated with a limited number of data points. The minimum number of data points required to fit a grey model is four observations. This package fits Grey model of First order and One Variable, i.e., GM (1,1) for multivariate time series data and returns the parameters of the model, model evaluation criteria and h-step ahead forecast values for each of the time series variables. For method details see, Akay, D. and Atak, M. (2007) <doi:10.1016/j.energy.2006.11.014>, Hsu, L. and Wang, C. (2007).<doi:10.1016/j.techfore.2006.02.005>.

Version:	0.1.0
Depends:	R (≥ 2.10)
Imports:	zoo, stats
Suggests:	knitr, rmarkdown, testthat (≥ 3.0.0)
Published:	2025-01-31
DOI:	10.32614/CRAN.package.MultiGrey
Author:	Pradip Basak [aut, cph, cre], Nobin Chandra Paul [aut, cph]
Maintainer:	Pradip Basak <pradip at ubkv.ac.in>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2.0)]
NeedsCompilation:	no
CRAN checks:	MultiGrey results

Documentation:

Reference manual:

MultiGrey.pdf

Downloads:

Package source:	MultiGrey_0.1.0.tar.gz
Windows binaries:	r-devel: MultiGrey_0.1.0.zip, r-release: MultiGrey_0.1.0.zip, r-oldrel: MultiGrey_0.1.0.zip
macOS binaries:	r-release (arm64): MultiGrey_0.1.0.tgz, r-oldrel (arm64): not available, r-release (x86_64): MultiGrey_0.1.0.tgz, r-oldrel (x86_64): not available

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