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.
- Version0.1.0
- R versionR (≥ 2.10)
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?No
- Last release01/31/2025
Team
Pradip Basak
MaintainerShow author detailsNobin Chandra Paul
Show author detailsRolesAuthor, Copyright holder
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- Imports1 package
- Suggests3 packages