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.


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0.1.3 by Bijan Seyednasrollah, 3 years ago

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Authors: Bijan Seyednasrollah , Jennifer J. Swenson , Jean-Christophe Domec , James S. Clark

Documentation:   PDF Manual  

MIT + file LICENSE license

Imports rjags

Suggests knitr, rmarkdown

See at CRAN