Using the Bayesian state-space approach, we developed a continuous development model to quantify dynamic incremental changes in the response variable. While the model was originally developed for daily changes in forest green-up, the model can be used to predict any similar process. The CDM can capture both timing and rate of nonlinear processes. Unlike statics methods, which aggregate variations into a single metric, our dynamic model tracks the changing impacts over time. The CDM accommodates nonlinear responses to variation in predictors, which changes throughout development.
Version: | 0.1.3 |
Depends: | R (≥ 3.3.0) |
Imports: | rjags |
Suggests: | knitr, rmarkdown |
Published: | 2018-05-02 |
DOI: | 10.32614/CRAN.package.phenoCDM |
Author: | Bijan Seyednasrollah, Jennifer J. Swenson, Jean-Christophe Domec, James S. Clark |
Maintainer: | Bijan Seyednasrollah <bijan.s.nasr at gmail.com> |
BugReports: | https://github.com/bnasr/phenoCDM/issues |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Citation: | phenoCDM citation info |
CRAN checks: | phenoCDM results |
Reference manual: | phenoCDM.pdf |
Vignettes: |
Getting started with phenoCDM |
Package source: | phenoCDM_0.1.3.tar.gz |
Windows binaries: | r-devel: phenoCDM_0.1.3.zip, r-release: phenoCDM_0.1.3.zip, r-oldrel: phenoCDM_0.1.3.zip |
macOS binaries: | r-release (arm64): phenoCDM_0.1.3.tgz, r-oldrel (arm64): phenoCDM_0.1.3.tgz, r-release (x86_64): phenoCDM_0.1.3.tgz, r-oldrel (x86_64): phenoCDM_0.1.3.tgz |
Old sources: | phenoCDM archive |
Please use the canonical form https://CRAN.R-project.org/package=phenoCDM to link to this page.