plot.aicsums

an object of class <code>aicsums</code>, as produced by <code><a rd-options="optimus" href="/link/find_optimal?package=optimus&version=0.2.0&to=optimus" data-mini-rdoc="optimus::find_optimal">find_optimal</a></code>.

additional arguments to pass to <code><a rd-options="graphics" href="/link/plot?package=optimus&version=0.2.0&to=graphics" data-mini-rdoc="graphics::plot">plot</a></code>.

S3 <code><a rd-options="" href="/link/plot?package=optimus&version=0.2.0" data-mini-rdoc="optimus::plot">plot</a></code> method for sum-of-AIC results from <code><a rd-options="optimus" href="/link/find_optimal?package=optimus&version=0.2.0&to=optimus" data-mini-rdoc="optimus::find_optimal">find_optimal</a></code>.

Assessment and diagnostics for comparing competing
clustering solutions, using predictive models. The main intended
use is for comparing clustering/classification solutions of
ecological data (e.g. presence/absence, counts, ordinal scores) to
1) find an optimal partitioning solution, 2) identify
characteristic species and 3) refine a classification by merging
clusters that increase predictive performance. However, in a more
general sense, this package can do the above for any set of
clustering solutions for i observations of j variables.

Mitchell Lyons

optimus

Model Based Diagnostics for Multivariate Cluster Analysis

plot.aicsums function

an object of class <code>aicsums</code>, as produced by <code><a rd-options='optimus' href='find_optimal'>find_optimal</a></code>.

additional arguments to pass to <code><a rd-options='graphics' href='plot'>plot</a></code>.

S3 <code><a rd-options='' href='plot'>plot</a></code> method for sum-of-AIC results from <code><a rd-options='optimus' href='find_optimal'>find_optimal</a></code>.

plot.aicsums: Plot sum-of-AIC results

Description

Usage

Arguments

Value

Examples