PDEplot: PDE plot

In DataVisualizations: Visualizations of High-Dimensional Data

PDE plot

Description

This function plots the Pareto probability density estimation (PDE), uses PDEstimationForGauss and ParetoRadius.

Usage

PDEplot(Data, paretoRadius = 0, weight = 1, kernels = NULL,

                 LogPlot = F, PlotIt = TRUE, title =
                 "ParetoDensityEstimation(PDE)", color = "blue",
				 
                 xpoints = FALSE, xlim, ylim, xlab, ylab =
                 "PDE", ggPlot = ggplot(), sampleSize = 2e+05, lwd = 2)
				 

Arguments

Data	[1:n] numeric vector of data to be plotted.
paretoRadius	numeric, the Pareto Radius. If omitted, calculate by paretoRad.
weight	numeric, Weight*ParetoDensity is plotted. 1 by default.
kernels	numeric vector of kernels. Optional
LogPlot	LogLog PDEplot if TRUE, xpoints has to be FALSE. Optional
PlotIt	logical, if plot. TRUE by default.
title	character vector, title of plot.
color	character vector, color of plot.
xpoints	logical, if TRUE only points are plotted. FALSE by default.
xlim	Arguments to be passed to the plot method.
ylim	Arguments to be passed to the plot method.
xlab	Arguments to be passed to the plot method.
ylab	Arguments to be passed to the plot method.
ggPlot	ggplot2 object to be plotted upon. Insert an exisiting plot to add a new PDEPlot to it. Default: empty plot
sampleSize	default(200000), sample size, if datavector is to big
lwd	linewidth, see plot

Value

kernels	numeric vector. The x points of the PDE function.
paretoDensity	numeric vector, the PDE(x).
paretoRadius	numeric value, the Pareto Radius used for the plot.
ggPlot	ggplot2 object. Can be used to further modify the plot or add other plots.

Author(s)

Michael Thrun

References

Ultsch, A.: Pareto Density Estimation: A Density Estimation for Knowledge Discovery, Baier D., Wernecke K.D. (Eds), In Innovations in Classification, Data Science, and Information Systems - Proceedings 27th Annual Conference of the German Classification Society (GfKL) 2003, Berlin, Heidelberg, Springer, pp, 91-100, 2005.

Examples

x <- rnorm(1000, mean = 0.5, sd = 0.5)
y <- rnorm(750, mean = -0.5, sd = 0.75)
plt <- PDEplot(x, color = "red")$ggPlot
plt <- PDEplot(y, color = "blue", ggPlot = plt)$ggPlot

# Second Example
#  ggplotObj=ggplot()
#  for(i in 1:length(Variables))
#     ggplotObj=PDEplot(Data[,i],ggPlot = ggplotObj)$ggPlot

DataVisualizations documentation built on Oct. 10, 2023, 9:06 a.m.