steepness package allows users to quantify and test steepness of dominance hierarchies with R.
5th May 2022
You can install the latest development version of steepness using devtools:
install.packages("devtools", dep = TRUE)
library(devtools)
install_github("DLEIVA/steepness")
library(steepness)
The latest release of steepness is available on CRAN:
install.packages("steepness", dep = TRUE)
library(steepness)
Running steepness test by means of a randomization procedure, summarizing and ploting results. Example taken from Vervaecke et al. (2007):
X <- matrix(c(0,58,50,61,32,37,29,39,25,8,0,22,22,9,27,20,10,48,
3,3,0,19,29,12,13,19,8,5,8,9,0,33,38,35,32,57,
4,7,9,1,0,28,26,16,23,4,3,0,0,6,0,7,6,12,
2,0,4,1,4,4,0,5,3,0,2,1,1,5,8,3,0,10,3,1,3,0,0,4,1,2,0),
nrow=9,byrow=TRUE)
individuals <- c("V","VS","B","FJ","PR","VB","TOR","MU","ZV")
STP <- steeptest(X, rep=9999, names=individuals, method="Dij", order=TRUE)
summary(STP)
plot(STP)
Happy to hear about issues you encounter using steepness via Github's issue tracker.
If you would like to submit a patch to improve steepness, please send a pull request to the develop branch.
Some improvements in steep.c file for compatibility with R>=2.15.3. .First.Lib replaced by .onLoad function.
First public version in CRAN
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