Package: phenoCDM 0.1.3
Bijan Seyednasrollah
phenoCDM: Continuous Development Models for Incremental Time-Series Analysis
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.
Authors:
phenoCDM_0.1.3.tar.gz
phenoCDM_0.1.3.tar.gz(r-4.5-noble)phenoCDM_0.1.3.tar.gz(r-4.4-noble)
phenoCDM_0.1.3.tgz(r-4.4-emscripten)phenoCDM_0.1.3.tgz(r-4.3-emscripten)
phenoCDM.pdf |phenoCDM.html✨
phenoCDM/json (API)
| # Install 'phenoCDM' in R: |
| install.packages('phenoCDM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bnasr/phenocdm/issues
Last updated 7 years agofrom:bb6ad3eba4. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 04 2024 |
| R-4.5-linux | OK | Dec 04 2024 |
Exports:fitCDMgetGibbsSummaryphenoSimphenoSimPlotplotPOGibbsplotPost
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit a CDM Model | fitCDM |
| Summarize Output of the CDM Model | getGibbsSummary |
| Simulate Green-up Phenology Data | phenoSim |
| Plot Simulated Phenology Data | phenoSimPlot |
| Plot Observed vs Predicted | plotPOGibbs |
| Plot Posterior Distributions | plotPost |
