Description Usage Arguments Value See Also Examples
Computes the between-group covariance matrix. The effect of sexual dimorphism can be removed by using, for each group, the average of the mean of males and the mean of females.
1 |
X |
a data matrix with variables in columns and group names as row names |
groups |
a character / factor vector containing grouping variable |
sex |
NULL (default). A character / factor vector containing sex variable, to remove sexual dimorphism by averaging males and females in each group |
center |
either a logical value or a numeric vector of length equal to the number of columns of X |
weighted |
logical. Should the between-group covariance matrix be weighted? |
The between-group covariance matrix
1 2 3 4 5 6 7 8 9 10 | # Data matrix of 2D landmark coordinates
data("Tropheus.IK.coord")
coords <- which(names(Tropheus.IK.coord) == "X1"):which(names(Tropheus.IK.coord) == "Y19")
proc.coord <- as.matrix(Tropheus.IK.coord[coords])
# Between-group covariance matrix for all populations
B <- cov.B(proc.coord, groups = Tropheus.IK.coord$POP.ID)
# Between-group covariance matrix for all populations, pooled by sex
B.mf <- cov.B(proc.coord, groups = Tropheus.IK.coord$POP.ID, sex = Tropheus.IK.coord$Sex)
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