hzar.dBernoulli.LL: Transformations of Scalar Data into Bernoulli Trials
In hzar: Hybrid Zone Analysis using R

Description Usage Arguments Details Value Author(s) See Also

View source: R/27-prepBernoulliTransform.R

This method operates on a collection of sampled scalar values and the sample localition site factor. It calculates a score for each "cut" value that can split the samples into unique groups, and either returns those scores, the cut value with the best score, or a table of the frequencies of the sample values that are less than the cut value with the best score.

1	hzar.dBernoulli.LL(values, locations, getMax = FALSE, getProbs = FALSE)

`values`	The sample values to use.
`locations`	The factor grouping sample values by location.
`getMax`	Should this method return the best cut value?
`getProbs`	Should this method return the table of frequencies of sample values which are less than the best cut value?

The score for a cut value is the information of learning the location of a sample conditioned on the knowledge of the whether the sample value is greater or less than the cut value. This score indicates how little a cut value distinguishes between localities.

The best scoring cut value is the one that determines the greatest amount of information about the sample location and therefore it is the one with lowest score.

Either a vector of scores, a single cut value, or a table of frequencies of the sample values that are less than the cut value with the best score.

Graham Derryberry asterion@alum.mit.edu

hzar.doMorphoSets hzar.obsData

hzar documentation built on May 2, 2019, 7 a.m.