Rank and Social Hierarchy for Gregarious Animals"
In socialh: Rank and Social Hierarchy for Gregarious Animals

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Description

The "socialh" package is a set of functions developed to facilitate the establishment of the rank and social hierarchy for gregarious animals by the Si method developed by Kondo & Hurnik (1990). It is also possible to determine the number of agonistic interactions between two individuals, sociometric and dyadics matrix from dataset obtained through electronic bins.

Function description

Function | Description ----------------|------------ replacement |Identify replacements between actor and reactor from electronic bins data. smatrix |Build a square matrix contained dyadic frequency of dominance-related behaviors. dmatrix |Determine the Sij dyadic dominance relationship from a sociomatrix. dvalue |Determine the dominance value, social rank and hierarchy from Sij dyadic. landau_index |Calculate the linearity index developed by Landau (1951). devries_index |Calculate the linearity index improved by de Vries (1995).

Application

#First, install and load the socialh R package
install.packages(socialh)
library(socialh)

#Load the dataset
exemple.data <- read.csv(behaviour_data.csv)

# Apply the replacement(x, sec) function to create a data table with actor and reactor and save as an object to use later.
replace <- replacement (exemple.data, 14)
head(replace)

#Use the smatrix() function to create sociometrix by a replacemente data table and save as an object to use later. 
social <- smatrix (replace)
head(social)

#            actor
#  reactor   2164251 2164252 2164255 2164259 2164261 2164263 
#  2164251      0      32      62      17      37      23
#  2164252     43       0      10      19       8      14
#  2164255     56      12       0       7      26      16
#  2164259     15       5      10       0       3      10
#  2164261     34       9      37       6       0      15
#  2164263     26      16      16      11       8       0

#Apply the dmatrix()function to transform the sociometrix in a dyadic matrix and save as an object to use later.
dyadic <- dmatrix (social)
head(dyadic)

#            actor
#  reactor   2164251 2164252 2164255 2164259 2164261 2164263 
#  2164251       0      -1       1       1       1      -1
#  2164252       1       0      -1       1      -1      -1
#  2164255      -1       1       0      -1      -1       0
#  2164259      -1      -1       1       0      -1      -1
#  2164261      -1       1       1       1       0       1
#  2164263       1       1       0       1      -1       0

#Employ the dvalue()function to determine dominance value, social rank and social hierarchy by a dyadic matrix.
dominance <- dvalue (dyadic)
head(dominance)
#   dominance_value animal_id social_hierarchy social_rank
#1:       -46        2164494     subordinate     lower
#2:       -37        2164490     subordinate     lower
#3:       -36        2164482     subordinate     lower
#4:       -30        2164477     subordinate     lower
#5:       -28        2164265     subordinate     lower
#6:       -27        2164529     subordinate     lower
tail(dominance)
#   dominance_value animal_id social_hierarchy social_rank
#1:        23        2164285     dominant        high
#2:        26        2164381     dominant        high
#3:        27        2164332     dominant        high
#4:        29        2164308     dominant        high
#5:        30        2164267     dominant        high
#6:        35        2164321     dominant        high

#Apply the landau_index()function to determine the linearity index by a dyadic matrix.
landau <- landau_index (dyadic)
print(landau)
#[1] 0.1743385

#Apply the devries_index()function to determine the improved linearity index by a dyadic matrix and a sociomatrix.
devries <- landau_index (dyadic, social)
print(devries)
#[1] 0.1754908