hierformR
Hierarchy Network Formation
Authors - James P. Curley (Columbia University) & Ivan D. Chase (Stony Brook University)
R Code for analyzing social hierarchy and network formation. Based upon algorithms described in Lindquist & Chase, 2009, Bulletin of Mathematical Biology
- "Data-Based Analysis of Winner-Loser Models of Hierarchy Formation in Animals" -
http://link.springer.com/article/10.1007%2Fs11538-008-9371-9
Installation
library(devtools)
devtools::install_github("jalapic/hierformR")
library(hierformR)Quick Example
Example dataframe of winners and losers:
df<-data.frame(winner=c(1,2,3,1,2,3,2,1,2,3,3,1,2,3,4,3,1,3,2,1,1,1,1,2,2),
loser=c(2,4,4,4,3,2,1,3,3,4,4,2,3,2,3,4,2,4,3,3,3,2,2,4,3)
)
winner loser
1 1 2
2 2 4
3 3 4
4 1 4
5 2 3
6 3 2
7 2 1
8 1 3
9 2 3
10 3 4
11 3 4
12 1 2
13 2 3
14 3 2
15 4 3
16 3 4
17 1 2
18 3 4
19 2 3
20 1 3
21 1 3
22 1 2
23 1 2
24 2 4
25 2 3
For each row, get last interaction between each pair of nodes - return a list of same length as df
lastints(df)Get directed network object based on most recent interactions between each pair of nodes
lastnet(df)Return the characteristics of the network relevant for determining its current state
gs <- lastnet(df)
g <- gs[[25]]
netchar(g)
X003 X012 X021D X021U X021C X030T X030C maxdom noedges nonodes distance degreediff
0 0 0 0 0 4 0 3 6 4 1 3
The most useful function is addstates. This will take any winner-loser dataframe and add the id and class of the states. Note - whilst the functions above work for directed networks of any size, this function is specifically for networks with four nodes:
addstates(df)
winner loser id class
1 1 2 1 1
2 2 4 3 L
3 3 4 13 C
4 1 4 22 Ht
5 2 3 32 Ft
6 3 2 33 Ft
7 2 1 32 Ft
8 1 3 40 Si
9 2 3 38 St
10 3 4 38 St
11 3 4 38 St
12 1 2 38 St
13 2 3 38 St
14 3 2 38 St
15 4 3 39 Si
16 3 4 38 St
17 1 2 38 St
18 3 4 38 St
19 2 3 38 St
20 1 3 38 St
21 1 3 38 St
22 1 2 38 St
23 1 2 38 St
24 2 4 38 St
25 2 3 38 StContact me at: jc3181 AT columbia DOT edu