Skip to contents

Evaluate region numbers

ps_regions_eval.Rd

This function compares multiple potential values for k, the number of clusters in to use in ps_regions(), to help you decide how well different numbers of regions fit your data set. For each value of k, it performs a cluster analysis and calculates the proportion of total variance explained (SSE, the sum of squared pairwise distances explained). It also calculates second-order metrics of the relationship between k and SSE. While many data sets have no optimal value of k and the choice is often highly subjective, these evaluation metrics can help you identify potential points where the variance explained stops increasing quickly as k increases.

Usage

ps_regions_eval(ps, k = 1:20, plot = TRUE, ...)

Arguments

ps

A phylospatial object. Must contain a dissim component generated by ps_add_dissim.

k

Vector of positive integers giving possible values for k. Values greater than the number of sites in the data set will be ignored.

plot

Logical indicating whether to print a plot of the results (TRUE, the default) or return a data frame of the results (FALSE).

...

Further arguments passed to ps_regions.

Value

The function generates a data frame with the following columns. If plot = FALSE the data frame is returned, otherwise the function prints a plot of the latter variables as a function of k:

  • "k": The number of clusters.

  • "sse": The proportion of total variance explained, with variance defined as squared pairwise community phylogenetic dissimilarity between sites.

  • "curvature": The local second derivative. Lower (more negative) values indicate more attractive break-point values of k.

  • "dist11": The distance from the point to the 1:1 line on a plot of k vs sse in which k values over the interval from 1 to the number of sites are rescaled to the unit interval. Higher values indicate more attractive values for k.

Examples

ps <- ps_add_dissim(ps_simulate())
ps_regions_eval(ps, k = 1:15, plot = TRUE)