hypervolume: Hypervolume construction methods

View source: R/hypervolume.R

hypervolumeR Documentation

Hypervolume construction methods

Description

Constructs hypervolumes using one of several possible methods after error-checking input data.

Usage

hypervolume(data, method = "gaussian", ...)

Arguments

data

A m x n matrix or data frame, where m is the number of observations and n is the dimensionality.

method

One of "box" (box kernel density estimation), "gaussian" (Gaussian kernel density estimation), or "svm" (one-class support vector machine). See respective functions for details.

...

Further arguments passed to hypervolume_box, hypervolume_gaussian, or hypervolume_svm.

Details

Checks for collinearity, missingness of input data, and appropriate random point coverage. Generates warning/errors as appropriate.

Value

A Hypervolume-class object corresponding to the inferred hypervolume.

See Also

weight_data, estimate_bandwidth, expectation_convex, expectation_ball, expectation_box, hypervolume_threshold

Examples

data(penguins,package='palmerpenguins')
penguins_no_na = as.data.frame(na.omit(penguins))
penguins_adelie = penguins_no_na[penguins_no_na$species=="Adelie",
                    c("bill_length_mm","bill_depth_mm","flipper_length_mm")]
hv = hypervolume(penguins_adelie,method='box')

hypervolume documentation built on May 17, 2022, 1:06 a.m.