get_di_matrix(m, type = "wl")type="wl" is the default which returns a win-loss matrix
with a '1' representing a consistent winner and a '0' representing a
consistent loser for each dyad of the matrix. A consistent winner is
defined as being the individual in each dyad that has absolutely more
wins than defeats. In the default condition if competitors have the
same number of wins each, they both receive a 0.
If type="wlties" the default dichotomized win-loss
matrix will be returned but it will also return 0.5 into cells for tied
relationships.
If type="wlties0" the default dichotomized win-loss
matrix will be returned but it will also return 0.5 into cells for tied
relationships. Additionally, if two competitors never interacted both
cells for that relationship will be returned with a 0.
If type="wlbinom" every relationship within the win-loss
matrix is assessed for whether one competitor significantly wins more
competitive interactions than the other competitor. Significance is
calculated using a binomial test with probability of p=0.05. A '1' is
given to significant winners within a relationship and a '0' is given
to significant losers or if neither individual is a winner.
If type="wlbinomties" The same procedure is done as for
type="wlbinom", but if no signficiant winner/loser can
be determined then a 0.5 is returned rather than a 0.
If type="pa" the inputted matrix will be turned into a
dichotomized presence-absence matrix, with a '1' indicating that the
competitor in a the row of the matrix beat the competitor in the column
at least once. A '0' indicates that that competitor never beat the
other competitor.
If type="dom" the inputted matrix will be turned into a
dominance score matrix, with a '1' indicating that the
competitor in a the row of the matrix dominates the competitor in the
column. A '-1' indicates that that competitor in a row is subordinate
to the competitor in the column. A '0.5' indicates a tie. A '0'
indicates an observational or structural zero.get_di_matrix(bonobos)
get_di_matrix(mouse)
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