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.

Version: 0.1.0
Depends: R (≥ 2.6), stats
Published: 2021-09-23
Author: Mrinmoy Ray [aut, cre], K. N. Singh [ctb], Kanchan Sinha [ctb], Rajeev Ranjan Kumar [ctb], Prakash Kumar [ctb]
Maintainer: Mrinmoy Ray <mrinmoy4848 at gmail.com>
License: GPL-3
NeedsCompilation: no
CRAN checks: tsfngm results


Reference manual: tsfngm.pdf


Package source: tsfngm_0.1.0.tar.gz
Windows binaries: r-devel: tsfngm_0.1.0.zip, r-release: tsfngm_0.1.0.zip, r-oldrel: tsfngm_0.1.0.zip
macOS binaries: r-release (arm64): tsfngm_0.1.0.tgz, r-oldrel (arm64): tsfngm_0.1.0.tgz, r-release (x86_64): tsfngm_0.1.0.tgz, r-oldrel (x86_64): tsfngm_0.1.0.tgz


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