prabclus: regdistdiff – R documentation

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regdistdiff

Regression difference between within-group dissimilarities

Description

Given two dissimilarity matrices dmx and dmy, an indicator vector x and a grouping, this computes the difference between standard least squares regression predictions at point xcenterbetween. The regressions are based on the dissimilarities in dmx vs. dmy for objects indicated in x. grouping indicates the two groups, and the difference is computed between regressions based on the within-group distances of the two groups.

Usage

regdistdiff(x,dmx,dmy,grouping,xcenter=0,xcenterbetween=0)

Arguments

`x`	vector of logicals of length of the number of objects on which dissimilarities `dmx` and `dmy` are based.
`dmx`	dissimilarity matrix or object of class `dist`. Explanatory dissimilarities.
`dmy`	dissimilarity matrix or object of class `dist`. Response dissimilarities.
`grouping`	vector of length of the number of objects on which dissimilarities `dmx` and `dmy` are based. Grouping vector. Regressions will be based on the first two values that appear in `unique(grouping[x])` (note that objects that are not assigned to one of these groups will be ignored); normally `grouping` should indicate only two groups on the objects with `x=TRUE`, and then these are used.
`xcenter`	numeric. Dissimilarities `dmx` are centered by this, i.e., this value is subtracted from the dissimilarities before regression.
`xcenterbetween`	numeric. This specifies the x- (dissimilarity) value at which predictions from the two regressions are compared. Note that this is interpreted as after centering by `xcenter`.

Value

Difference between standard least squares regression predictions for the two groups at point xcenterbetween.

Author(s)

Christian Hennig christian.hennig@unibo.it https://www.unibo.it/sitoweb/christian.hennig/en

References

Hausdorf, B. and Hennig, C. (2019) Species delimitation and geography. Submitted.

Examples

options(digits=4)
  data(veronica)
  ver.geo <- coord2dist(coordmatrix=veronica.coord[173:207,],file.format="decimal2")
  vei <- prabinit(prabmatrix=veronica[173:207,],distance="jaccard")

  species <-c(rep(1,13),rep(2,22))
  regdistdiff(rep(TRUE,35),ver.geo,vei$distmat,grouping=species,xcenter=0,xcenterbetween=100)

prabclus

Functions for Clustering and Testing of Presence-Absence, Abundance and Multilocus Genetic Data

v2.3-2

GPL

Authors

Christian Hennig <christian.hennig@unibo.it>, Bernhard Hausdorf <Hausdorf@zoologie.uni-hamburg.de>

Initial release

2020-01-06