BFAST integrates the decomposition of time series into
trend, seasonal, and remainder components with methods for
detecting and characterizing abrupt changes within the trend
and seasonal components. BFAST can be used to analyze different
types of satellite image time series and can be applied to
other disciplines dealing with seasonal or non-seasonal time
series, such as hydrology, climatology, and econometrics. The
algorithm can be extended to label detected changes with
information on the parameters of the fitted piecewise linear
models. BFAST monitoring functionality is added based on a
paper that has been submitted to Remote Sensing of Environment.
BFAST monitor provides functionality to detect disturbance in
near real-time based on BFAST-type models.
| Version: |
1.4.4 |
| Depends: |
R (≥ 2.0.0), graphics, stats, strucchange, MASS, forecast, zoo, raster, sp |
| Imports: |
graphics, stats, strucchange, zoo, raster |
| Published: |
2013-03-27 |
| Author: |
Jan Verbesselt [aut, cre], Achim Zeileis [aut], Rob Hyndman
[ctb], Rogier De Jong [ctb] |
| Maintainer: |
Jan Verbesselt <Jan.Verbesselt at wur.nl> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
http://bfast.R-Forge.R-project.org/ |
| NeedsCompilation: |
no |
| Citation: |
bfast citation info |
| In views: |
TimeSeries |
| CRAN checks: |
bfast results |