Package: MultiGrey 0.1.0

Pradip Basak

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>.

Authors:Pradip Basak [aut, cph, cre], Nobin Chandra Paul [aut, cph]

MultiGrey_0.1.0.tar.gz
MultiGrey_0.1.0.tar.gz(r-4.5-noble)MultiGrey_0.1.0.tar.gz(r-4.4-noble)
MultiGrey_0.1.0.tgz(r-4.4-emscripten)MultiGrey_0.1.0.tgz(r-4.3-emscripten)
MultiGrey.pdf |MultiGrey.html
MultiGrey/json (API)

# Install 'MultiGrey' in R:
install.packages('MultiGrey', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.00 score 2 exports 2 dependencies

Last updated 20 days agofrom:28b3871d1c. Checks:2 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKJan 31 2025
R-4.5-linuxOKJan 31 2025

Exports:multigreyfitmultigreyforecast

Dependencies:latticezoo