Description Usage Arguments Value See Also Examples
View source: R/axial_helper_functions.R
This function performs an estimation of axial dispersal for a numeric vector of distances between close kin dyads with confidence
intervals. The axial dispersal distance returned is interpretable as the standard deviation of one dimension of a
symmetric bivariate random distribution centred on zero. Confidence intervals are assigned via bootstrapping, or optionally the
vector of all bootstrapped results can be outputted by setting output
to 'vect'
, enabling its passing to other
functions or external statistical analysis.
1 | axpermute(vals, nreps = 1000, nsamp = "std", composite = 1, output = "confs")
|
vals |
numeric. Vector of distances between close kin OR object of class KinPairData. |
nreps |
numeric. Number of permutations to run for confidence intervals (default 1000) |
nsamp |
numeric. Number of kin pairs to subsample for each permutation. Either "std" or an integer. If "std" will be computed as equal to the sample size. (default "std") |
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) |
output |
character. Denotes what kind of output to return. If 'confs', a vector of 95% confidence intervals. if 'vect', a vector of all permuted axial value results |
If ouput = 'confs', returns a numeric vector
of 95% confidence intervals and mean axial value.
if output = 'vect', returns a numeric vector
of all permuted axial value results
Other axial_helpers:
axials_add()
,
axials_decompose()
,
axials_subtract()
,
axials()
,
axpermute_subtract()
1 2 | |
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