Package: MultiGrey 0.1.0
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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:
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.
Last updated 20 days agofrom:28b3871d1c. Checks:2 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Jan 31 2025 |
R-4.5-linux | OK | Jan 31 2025 |
Exports:multigreyfitmultigreyforecast
Readme and manuals
Help Manual
Help page | Topics |
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Fit the GM (1, 1) model for multivariate time series data | multigreyfit |
Forecast the GM (1, 1) model for multivariate time series data | multigreyforecast |