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MultiGrey  

Fitting and Forecasting of Grey Model for Multivariate Time Series Data
View on CRAN: Click here


Download and install MultiGrey package within the R console
Install from CRAN:
install.packages("MultiGrey")

Install from Github:
library("remotes")
install_github("cran/MultiGrey")

Install by package version:
library("remotes")
install_version("MultiGrey", "0.1.0")



Attach the package and use:
library("MultiGrey")
Maintained by
Pradip Basak
[Scholar Profile | Author Map]
First Published: 2025-01-31
Latest Update: 2025-01-31
Description:
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>.
How to cite:
Pradip Basak (2025). MultiGrey: Fitting and Forecasting of Grey Model for Multivariate Time Series Data. R package version 0.1.0, https://cran.r-project.org/web/packages/MultiGrey. Accessed 01 May. 2025.
Previous versions and publish date:
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Complete documentation for MultiGrey
Functions, R codes and Examples using the MultiGrey R package
Full MultiGrey package functions and examples
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