kindisperse (version 0.10.2)

axials: Estimate the axial dispersal distance of a kernel

Description

This function performs a basic estimation of axial dispersal for a numeric vector of distances between close kin dyads. The axial dispersal distance returned is interpretable as the standard deviation of one dimension of a symmetric bivariate random distribution centred on zero.

Usage

axials(valvect, composite = 1)

Arguments

valvect

A numeric vector of distances between close kin OR an object of class KinPairData

composite

numeric. The number of separate 'draws' (dispersal events) from the kernel required to produce the final positions of the measured individuals. For example, the displacement of a child from parent at the same lifestage would involve 1 draw and thus be composite = 1. Two full siblings would be two draws (composite = 2) from the FS kernel. Non-symmetric relationships (e.g. AV, 1C) should not be decomposed using this method, nor should any assumptions be made about different kernels (e.g. the 1C relationship would appropriately be given the value 2, but not 4)

Value

Returns the value of the estimated axial dispersal distance of the kernel producing the dispersal distances measured. (numeric)

See Also

Other axial_helpers: axials_add(), axials_decompose(), axials_subtract(), axpermute_subtract(), axpermute()

Examples

# NOT RUN {
po_dists <- c(5, 6, 7.5)
axials(po_dists) # one 'draw' (dispersal event) goes into the parent offspring category
# so composite is left to its default of 1

fs_dists <- c(2, 3, 3)
axials(fs_dists, composite = 2) # two 'draws' (symmetric dispersal events)
# go into the full sibling category so composite is set to 2
# }