PDEplot function

PDE plot

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

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

Returns

• 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.

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.

Author(s)

Michael Thrun

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