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binomialtrend  

Calculates the Statistical Significance of a Trend in a Set of Measurements
View on CRAN: Click here


Download and install binomialtrend package within the R console
Install from CRAN:
install.packages("binomialtrend")

Install from Github:
library("remotes")
install_github("cran/binomialtrend")

Install by package version:
library("remotes")
install_version("binomialtrend", "0.0.0.3")



Attach the package and use:
library("binomialtrend")
Maintained by
Matthew Cserhati
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-19
Latest Update: 2022-12-19
Description:
Detection of a statistically significant trend in the data provided by the user. This is based on the a signed test based on the binomial distribution. The package returns a trend test value, T, and also a p-value. A T value close to 1 indicates a rising trend, whereas a T value close to -1 indicates a decreasing trend. A T value close to 0 indicates no trend. There is also a command to visualize the trend. A test data set called gtsa_data is also available, which has global mean temperatures for January, April, July, and October for the years 1851 to 2022. Reference: Walpole, Myers, Myers, Ye. (2007, ISBN: 0-13-187711-9).
How to cite:
Matthew Cserhati (2022). binomialtrend: Calculates the Statistical Significance of a Trend in a Set of Measurements. R package version 0.0.0.3, https://cran.r-project.org/web/packages/binomialtrend. Accessed 12 Oct. 2026.
Previous versions and publish date:
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Complete documentation for binomialtrend
Functions, R codes and Examples using the binomialtrend R package
Some associated functions: binomialtrend . gsta_data . trendmap . 
Some associated R codes: binomialtrend.R . data.R . trendmap.R .  Full binomialtrend package functions and examples
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