Package: tsfngm 0.1.0

Mrinmoy Ray

tsfngm: Time Series Forecasting using Nonlinear Growth Models

Nonlinear growth models are extremely useful in gaining insight into the underlying mechanism. These models are generally 'mechanistic,' with parameters that have biological meaning. This package allows you to fit and forecast time series data using nonlinear growth models.

Authors:Mrinmoy Ray [aut, cre], K. N. Singh [ctb], Kanchan Sinha [ctb], Rajeev Ranjan Kumar [ctb], Prakash Kumar [ctb]

tsfngm_0.1.0.tar.gz
tsfngm_0.1.0.zip(r-4.7-any)tsfngm_0.1.0.zip(r-4.6-any)
tsfngm_0.1.0.tar.gz(r-4.7-any)tsfngm_0.1.0.tar.gz(r-4.6-any)
tsfngm_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
tsfngm/json (API)

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

On CRAN:

Conda:

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

1.00 score 206 downloads 1 exports 0 dependencies

Last updated from:448f7ed153. Checks:6 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK79
source / vignettesOK161
linux-releaseOK84
windows-develOK64
windows-releaseOK48
wasm-releaseOK71

Exports:FFNGM

Dependencies: