R: PDE plot

PDEplot {DataVisualizations} | R Documentation

## 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

[Package DataVisualizations version 1.2.3 Index]