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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>.

Versions across snapshots

VersionRepositoryFileSize
0.1.0 rolling linux/jammy R-4.5 MultiGrey_0.1.0.tar.gz 16.7 KiB
0.1.0 rolling linux/noble R-4.5 MultiGrey_0.1.0.tar.gz 16.6 KiB
0.1.0 rolling source/ R- MultiGrey_0.1.0.tar.gz 3.0 KiB
0.1.0 latest linux/jammy R-4.5 MultiGrey_0.1.0.tar.gz 16.7 KiB
0.1.0 latest linux/noble R-4.5 MultiGrey_0.1.0.tar.gz 16.6 KiB
0.1.0 latest source/ R- MultiGrey_0.1.0.tar.gz 3.0 KiB
0.1.0 2026-04-26 source/ R- MultiGrey_0.1.0.tar.gz 3.0 KiB
0.1.0 2026-04-23 source/ R- MultiGrey_0.1.0.tar.gz 3.0 KiB
0.1.0 2026-04-09 windows/windows R-4.5 MultiGrey_0.1.0.zip 19.5 KiB
0.1.0 2025-04-20 source/ R- MultiGrey_0.1.0.tar.gz 3.0 KiB

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