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DBEST
View on CRAN: Click
here
Download and install DBEST package within the R console
Install from CRAN:
install.packages("DBEST")
Install from Github:
library("remotes")
install_github("cran/DBEST")
Install by package version:
library("remotes")
install_version("DBEST", "1.8")
Attach the package and use:
library("DBEST")
Maintained by
Hristo Tomov
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2016-05-12
Latest Update: 2017-10-23
Description:
A program for analyzing vegetation time series, with two algorithms: 1) change detection algorithm that detects trend changes, determines their type (abrupt or non-abrupt), and estimates their timing, magnitude, number, and direction; 2) generalization algorithm that simplifies the temporal trend into main features. The user can set the number of major breakpoints or magnitude of greatest changes of interest for detection, and can control the generalization process by setting an additional parameter of generalization-percentage.
How to cite:
Hristo Tomov (2016). DBEST: Detecting Breakpoints and Estimating Segments in Trend. R package version 1.8, https://cran.r-project.org/web/packages/DBEST. Accessed 22 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for DBEST
Functions, R codes and Examples using
the DBEST R package
Some associated functions: DBEST . NDVI.Site1 . NDVI.Site2 . TREND.Site1 . TREND.Site2 . plot.DBEST .
Some associated R codes: BIC_BP.R . Compute_epsilon.R . DBEST-internal.R . DBEST.R . DBEST_timeseries_BP.R . DBEST_timeseries_Threshold.R . DETREND_SJ.R . Point_to_line.R . Pvalue_ith_coeff.R . Trend_local_change.R . f_level_shift.R . inv.R . mldivide.R . mrdivide.R . pinv.R . plot.DBEST.R . print.DBEST.R . Full DBEST package functions and examples
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