Package: bfast
Version: 1.5.7
Date: 2014-08-27
Title: Breaks For Additive Season and Trend (BFAST)
Authors@R: c(person(given = "Jan", family = "Verbesselt", role = c("aut", "cre"), email = "Jan.Verbesselt@wur.nl"),
             person(given = "Achim", family = "Zeileis", role = "aut", email = "Achim.Zeileis@R-project.org"),
             person(given = "Rob", family = "Hyndman", role = "ctb", email = "Rob.Hyndman@buseco.monash.edu.au"))
Author: Jan Verbesselt [aut, cre], Achim Zeileis [aut], Rob Hyndman [ctb]
Maintainer: Jan Verbesselt <Jan.Verbesselt@wur.nl>
Description: 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.
       BFAST approach is flexible approach that handles missing data without interpolation.
       Furthermore now different models can be used to fit the time series data and detect structural changes (breaks).
Depends: R (>= 2.15.0)
Imports: graphics, stats, strucchange, zoo, forecast, sp, raster
Suggests:
License: GPL (>= 2)
URL: http://bfast.R-Forge.R-project.org/
LazyLoad: yes
LazyData: yes
Repository: CRAN
Repository/R-Forge/Project: bfast
Repository/R-Forge/Revision: 464
Repository/R-Forge/DateTimeStamp: 2014-08-27 18:49:54
Date/Publication: 2014-08-28 00:00:24
Packaged: 2014-08-27 20:15:07 UTC; rforge
NeedsCompilation: no
