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trendchange
View on CRAN: Click
here
Download and install trendchange package within the R console
Install from CRAN:
install.packages("trendchange")
Install from Github:
library("remotes")
install_github("cran/trendchange") Install by package version:
library("remotes")
install_version("trendchange", "1.2") Attach the package and use:
library("trendchange")
Maintained by
Sandeep Kumar Patakamuri
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-01-20
Latest Update: 2022-01-08
Description:
Innovative Trend Analysis is a graphical method to examine the trends in time series data. Sequential Mann-Kendall test uses the intersection of prograde and retrograde series to indicate the possible change point in time series data. Distribution free cumulative sum charts indicate location and significance of the change point in time series. Zekai, S. (2011). <doi:10.1061/(ASCE)HE.1943-5584.0000556>. Grayson, R. B. et al. (1996). Hydrological Recipes: Estimation Techniques in Australian Hydrology. Cooperative Research Centre for Catchment Hydrology, Australia, p. 125. Sneyers, S. (1990). On the statistical analysis of series of observations. Technical note no 5 143, WMO No 725 415. Secretariat of the World Meteorological Organization, Geneva, 192 pp.
How to cite:
Sandeep Kumar Patakamuri (2019). trendchange: Innovative Trend Analysis and Time-Series Change Point Analysis. R package version 1.2, https://cran.r-project.org/web/packages/trendchange. Accessed 26 Aug. 2026.
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Complete documentation for trendchange
Functions, R codes and Examples using
the trendchange R package
Some associated functions: df . dfcusum . innovtrend . ipta . sqmk . x .
Some associated R codes: data.R . dfcusum.R . exampledf.R . innovtrend.R . ipta.R . sqmk.R . Full trendchange package functions and examples
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