CBI: Clutton-Brock et al 1979 index (CBI)
In EloRating: Animal Dominance Hierarchies by Elo Rating

Description Usage Arguments Details Value Author(s) References Examples

Clutton-Brock et al 1979 index (CBI)

CBI(mat)

mat

matrix

The results of this function diverge from published examples in some cases. While the function produces identical scores as the results in \insertCitegammell2003;textualEloRating and \insertCitedevries2000;textualEloRating there are some slight deviations for the example in \insertCitewhitehead2008;textualEloRating. The final example from \insertCitebang2010;textualEloRating is fairly off, but that seems to be because these authors might have applied different definitions: \insertCitebang2010;textualEloRating talk about 'who dominates' while \insertCiteclutton-brock1979EloRating consider 'who won interactions', which are two very different conceptualizations, and which might explain the discrepancies.

a named numeric vector with the indices for each individual

Christof Neumann

\insertRef

clutton-brock1979EloRating

\insertRef

bang2010EloRating

\insertRef

gammell2003EloRating

\insertRef

devries2000EloRating

\insertRef

whitehead2008EloRating

# example from Gammell et al 2003 (table 1)
m <- matrix(0, nrow = 5, ncol = 5)
m[upper.tri(m)] <- 100
m[1, 5] <- 99
m[5, 1] <- 1
colnames(m) <- rownames(m) <- c("r", "s", "t", "u", "v")
m
CBI(m)

# example from Whitehead 2008 (table 5.8, 5.9)
m <- c(0, 2, 0, 5, 2, 2, 1, 0, 2, 0,
       0, 0, 2, 2, 1, 0, 3, 2, 1, 1,
       0, 1, 0, 1, 1, 3, 1, 1, 4, 0,
       0, 0, 0, 0, 1, 1, 1, 0, 1, 0,
       0, 0, 0, 0, 0, 7, 1, 4, 2, 3,
       0, 0, 0, 0, 0, 0, 2, 3, 6, 10,
       0, 1, 1, 0, 2, 0, 0, 0, 0, 2,
       0, 0, 0, 1, 0, 0, 0, 0, 1, 1,
       0, 0, 0, 1, 0, 0, 0, 0, 0, 1,
       0, 0, 0, 0, 0, 0, 0, 0, 0, 0)
mat <- matrix(m, nrow = 10, byrow = TRUE)
colnames(mat) <- rownames(mat) <- c("x907", "x915", "x912", "x910", "x917",
                                    "x898", "x897", "x911", "x904", "x902")
round(CBI(mat), 2)
# results in book:
# 33, 2.75, 3.08, 0.91, 0.86, 0.82, 0.92, 0.53, 0.23, 0.03

simple_dom(mat2seq(mat)$winner, mat2seq(mat)$loser)

# example from Bang et al 2010 (table 1)
m <- c(0, 1, 0, 2,
       1, 0, 4, 0,
       2, 2, 0, 3,
       3, 0, 1, 0)
m <- matrix(m, ncol = 4, byrow = TRUE)
m <- t(m)
colnames(m) <- rownames(m) <- letters[1:4]
CBI(m)
# results in paper:
# 1.43, 1, 0.7, 1

# and from de Vries and Appleby (2000, table 4)
m <- c(0, 1, 1, 4, 0, 3, 6,
       0, 0, 1, 4, 0, 0, 0,
       0, 0, 0, 1, 1, 3, 14,
       0, 0, 0, 0, 2, 2, 1,
       0, 0, 0, 0, 0, 17, 2,
       0, 0, 0, 0, 0, 0, 12,
       0, 0, 0, 0, 0, 0, 0)
m <- matrix(m, ncol = 7, byrow = TRUE)
colnames(m) <- rownames(m) <- letters[1:7]
CBI(m)
simple_dom(mat2seq(m)$winner, mat2seq(m)$loser)

Loading required package: zoo

Attaching package: ‘zoo’

The following objects are masked from ‘package:base’:

    as.Date, as.Date.numeric

Loading required package: sna
Loading required package: statnet.common

Attaching package: ‘statnet.common’

The following object is masked from ‘package:base’:

    order

Loading required package: network
network: Classes for Relational Data
Version 1.16.1 created on 2020-10-06.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
                    Mark S. Handcock, University of California -- Los Angeles
                    David R. Hunter, Penn State University
                    Martina Morris, University of Washington
                    Skye Bender-deMoll, University of Washington
 For citation information, type citation("network").
 Type help("network-package") to get started.

sna: Tools for Social Network Analysis
Version 2.6 created on 2020-10-5.
copyright (c) 2005, Carter T. Butts, University of California-Irvine
 For citation information, type citation("sna").
 Type help(package="sna") to get started.

  r   s   t   u   v
r 0 100 100 100  99
s 0   0 100 100 100
t 0   0   0 100 100
u 0   0   0   0 100
v 1   0   0   0   0
        r         s         t         u         v 
2.2000000 2.6666667 1.0000000 0.3750000 0.4545455 
 x907  x915  x912  x910  x917  x898  x897  x911  x904  x902 
33.00  3.10  3.50  0.90  0.86  0.82  0.91  0.53  0.20  0.03 
     ID   winprop winprop_rank   domover domover_rank domover_rel
1  x897 0.4000000            6 0.2222222          8.0   0.2857143
2  x898 0.6176471            5 0.4444444          4.5   0.5000000
3  x902 0.0000000           10 0.0000000         10.0   0.0000000
4  x904 0.1052632            9 0.1111111          9.0   0.1250000
5  x907 1.0000000            1 0.6666667          2.0   1.0000000
6  x910 0.2857143            7 0.3333333          6.5   0.3750000
7  x911 0.2307692            8 0.3333333          6.5   0.4285714
8  x912 0.8000000            2 0.5555556          3.0   0.7142857
9  x915 0.7500000            3 0.7777778          1.0   0.8750000
10 x917 0.7083333            4 0.4444444          4.5   0.4444444
   domover_rel_rank
1                 8
2                 4
3                10
4                 9
5                 1
6                 7
7                 6
8                 3
9                 2
10                5
    a     b     c     d 
1.600 1.000 0.625 1.000 
          a           b           c           d           e           f 
16.00000000  5.00000000  2.75000000  1.00000000  0.50000000  0.16666667 
          g 
 0.05882353 
  ID   winprop winprop_rank   domover domover_rank domover_rel domover_rel_rank
1  a 1.0000000            1 0.8333333          1.0   1.0000000              1.0
2  b 0.8333333            4 0.3333333          4.5   0.6666667              2.5
3  c 0.9047619            2 0.6666667          2.0   0.6666667              2.5
4  d 0.3571429            5 0.5000000          3.0   0.5000000              4.5
5  e 0.8636364            3 0.3333333          4.5   0.5000000              4.5
6  f 0.3243243            6 0.1666667          6.0   0.2000000              6.0
7  g 0.0000000            7 0.0000000          7.0   0.0000000              7.0