Rendered from
MB.Rmdusingknitr::rmarkdown
Bushra Alsaeed
A new way to predict time series using the marginal distribution table in the absence of the significance of traditional models.
Authors:Mohamad-Taher Anan [aut], Mohamad Alawad [aut], Bushra Alsaeed [aut, cre]
MB_0.1.1.tar.gz
MB_0.1.1.tar.gz(r-4.7-any)MB_0.1.1.tar.gz(r-4.6-any)
MB_0.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
MB/json (API)
| # Install 'MB' in R: |
| install.packages('MB', 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.
2.00 score 8 scripts 266 downloads 1 exports 10 dependencies
Last updated from:242cfd6a43. Checks:2 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 111 | ||
| source / vignettes | OK | 158 | ||
| linux-release-x86_64 | NOTE | 110 | ||
| wasm-release | OK | 111 |
Exports:ff
Dependencies:cligluelifecyclemagrittrpillarpkgconfigrlangtibbleutf8vctrs