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.
- Version0.1.3
- R version≥ 3.3.0
- LicenseMIT
- Licensefile LICENSE
- Needs compilation?No
- phenoCDM citation info
- Last release05/02/2018
Documentation
Team
Bijan Seyednasrollah
Bijan Seyednasrollah, Jennifer J. Swenson, Jean-Christophe Domec, James S. Clark
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Depends1 package
- Imports1 package
- Suggests2 packages