--- title: "Rank and Social Hierarchy for Gregarious Animals" author: "Julia P S Valente, Matheus Deniz, Karolini T de Sousa" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{Rank and Social Hierarchy for Gregarious Animals} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- ```{r, include = FALSE} 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 ```