cov.B: Between-group covariance matrix

In vcvComp: Comparison of Variance - Covariance Patterns

Description

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.

Usage

cov.B(X, groups, sex = NULL, center = FALSE, weighted = FALSE)

Arguments

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?

Value

The between-group covariance matrix

See Also

cov, cov.wt

Examples

# 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)

vcvComp documentation built on Dec. 17, 2020, 9:07 a.m.