bfast: Breaks for Additive Season and Trend
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 described
in Verbesselt et al. (2010) <doi:10.1016/j.rse.2009.08.014>. 'BFAST monitor'
provides functionality to detect disturbance in near real-time based on 'BFAST'-
type models, and is described in Verbesselt et al. (2012) <doi:10.1016/j.rse.2012.02.022>.
'BFAST Lite' approach is a flexible approach that handles missing data
without interpolation, and will be described in an upcoming paper.
Furthermore, different models can now be used to fit the
time series data and detect structural changes (breaks).
| Version: |
1.6.1 |
| Depends: |
R (≥ 3.0.0), strucchangeRcpp |
| Imports: |
graphics, stats, zoo, forecast, Rcpp (≥ 0.12.7), Rdpack (≥
0.7) |
| LinkingTo: |
Rcpp |
| Suggests: |
MASS, sfsmisc, stlplus, raster |
| Published: |
2021-05-10 |
| Author: |
Jan Verbesselt [aut],
Dainius Masiliunas
 [aut, cre],
Achim Zeileis [aut],
Rob Hyndman [ctb],
Marius Appel [aut],
Martin Jung [ctb],
Andrei Mirt [ctb],
Paulo Negri Bernardino [ctb],
Dongdong Kong
[ctb] |
| Maintainer: |
Dainius Masiliunas <pastas4 at gmail.com> |
| BugReports: |
https://github.com/bfast2/bfast/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://bfast2.github.io/ |
| NeedsCompilation: |
yes |
| Citation: |
bfast citation info |
| Materials: |
NEWS |
| In views: |
TimeSeries |
| CRAN checks: |
bfast results |
Documentation:
Downloads:
Reverse dependencies:
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