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phenoCDM: Continuous Development Models for Incremental Time-SeriesAnalysis

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 + fileLICENSE
NeedsCompilation:no
Citation:phenoCDM citation info
CRAN checks:phenoCDM results

Documentation:

Reference manual:phenoCDM.html ,phenoCDM.pdf
Vignettes:Getting started with phenoCDM (source,R code)

Downloads:

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

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=phenoCDMto link to this page.


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