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kepdf-class

Class "kepdf"


Description

This class encapsulates results of the application of function kepdf.

Objects from the Class

Objects can be created by calls of the form new("kepdf", ...) or as a result of a call to kepdf.

Slots

call:

Object of class "call", corresponding to the matched call.

x:

Object of class "matrix" representing the data points used to estimate the probability density function.

eval.points:

Object of class "matrix" representing the data points at which the density is evaluated.

estimate

The values of the density estimate at the evaluation points.

kernel:

Object of class "character" giving the selected kernel.

bwtype:

Object of class "character" giving the selected type of estimator.

par:

Object of class "list" providing the parameters used to estimate the density. Its elements are h, hx, and possibly alpha.

See kepdf for further details.

Methods

plot

signature(x = "kepdf", y = "ANY")

Plots objects of kepdf-class. plot-methods are available for density estimates of:

  • one-dimensional data;

  • two-dimensional data: contour, image or perspective plots are available;

  • multi-dimensional data: matrix of plots of all the pairs of two-dimensional marginal kernel density estimates.

See plot,kepdf-method for further details.

show

signature(object = "kepdf")

Prints the following elements:

  • the class of the object;

  • the selected kernel;

  • the selected type of estimator;

  • either the fixed smoothing parameters or the smoothing parameters of each observation;

  • the density estimates at the evaluation points.

summary

signature(object = "kepdf")

Provides a summary of kepdf-class object by printing the highest density data point and the row or index position of a percentage top density data points, possibly given as optional argument prop.

See Also

Examples

#
showClass("kepdf")

#
data(wine)
#select only "Barolo"-type wines
x <- wine[1:59,3] 
pdf <- kepdf(x)
pdf
summary(pdf)
summary(pdf, props = 10*seq(1, 9, by = 1))

pdfCluster

Cluster Analysis via Nonparametric Density Estimation

v1.0-3
GPL-2
Authors
Adelchi Azzalini, Giovanna Menardi for the current version; Adelchi Azzalini, Giovanna Menardi and Tiziana Rosolin up to version 0.1-13.
Initial release
2018-12-04

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