pygrowthmodels
A compilation of nonlinear growth models
Features
pygrowthmodels includes functions for the calculation of the following nonlinear growth models and its inverse functions:
Blumberg
Brody
Chapman-Richards
Generalised Logistic
Generalised Richard
Gompertz
Janoschek
Log-logistic
Logistic
Mitcherlich
Monomolecular
Morgan-Mercer-Flodin
Negative exponential
Richard’s
Rosso
Schnute
Stannard
von Bertalanffy
Weibull
References
D. Fekedulegn, M. Mac Siurtain, and J. Colbert, “Parameter estimation of nonlinear growth models in forestry,” Silva Fennica, vol. 33, no. 4, pp. 327-336, 1999. Full text
M. M. Kaps, W. O. W. Herring, and W. R. W. Lamberson, “Genetic and environmental parameters for traits derived from the Brody growth curve and their relationships with weaning weight in Angus cattle.,” Journal of Animal Science, vol. 78, no. 6, pp. 1436-1442, May 2000. Full text
A. Tsoularis and J. Wallace, “Analysis of logistic growth models.,” Math Biosci, vol. 179, no. 1, pp. 21–55, Jul. 2002. DOI identifier: 10.1016/j.bbr.2011.03.031
A. Khamiz, Z. Ismail, and A. T. Muhammad, “Nonlinear growth models for modeling oil palm yield growth,” Journal of Mathematics and Statistics, vol. 1, no. 3, p. 225, 2005. DOI identifier: 10.3844/jmssp.2005.225.233
Michael J. Panik, “Growth Curve Modeling: Theory and Applications”, John Wiley & Sons, December 2013.
T. Ross, “Indices for performance evaluation of predictive models in food microbiology.” J. Appl. Bacteriol. vol. 81, no. 5, pp. 501–508. Nov. 1996.
Wikipedia contributors, “Generalised logistic function”, Wikipedia, The Free Encyclopedia, 6 April 2018, 16:27 UTC, accessed 6 April 2018
Disclaimer
Copyright (C) 2018 Daniel Rodríguez Pérez
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.
Metadata
Release files for pygrowthmodels 0.0.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| pygrowthmodels-0.0.3.tar.gz | 12.8 kB | Without provenance | Details for pygrowthmodels-0.0.3.tar.gz |
Release files / pygrowthmodels-0.0.3.tar.gz
| Download URL | pygrowthmodels-0.0.3.tar.gz |
|---|---|
| Size | 12.8 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
cf5828d563b7843009659d07a9c0f744090012a724400073fd6a28308c3a8298
|
|
BLAKE2b-256 checksum How to use checksums |
84dbb775dd6b333d5388443eb179e5890c5d14abc7b9192b8278e8cb6f06e533
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Security for pygrowthmodels 0.0.3
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.