PDEplot the data for allclasses, weight the Plot with 1 (= maximum likelihood)
ClassPDEplotMaxLikeli(Data, Cls, ColorSequence = DataVisualizations::DefaultColorSequence, ClassNames, PlotLegend = TRUE, MinAnzKernels = 0,PlotNorm,
main = "Pareto Density Estimation (PDE)",
xlab = "Data", ylab = "ParetoDensity", xlim, ylim, …)
The Data to be plotted
Vector of class identifiers. Can be integers or NaN's, need not be consecutive nor positive
Optional: the sequence of colors used, Default: DefaultColorSequence
Optional: the names of the classes to be displayed in the legend
Optional: add a legent to plot (default == 1)
Optional: Minimum number of kernels
Optional: ==1 => plot Normal distribuion on top , ==2 = plot robust normal distribution,; default: PlotNorm= 0
Optional: Title of the plot
Optional: title of the x axis
Optional: title of the y axis
Optional: area of the x-axis to be plotted
Optional: area of the y-axis to be plotted
further arguments passed to plot
Kernels of the distributions
Pareto densities for classes
ggplot2 plot object. This should be used to further modify the plot
Aubert, A. H., Thrun, M. C., Breuer, L., & Ultsch, A. : Knowledge discovery from high-frequency stream nitrate concentrations: hydrology and biology contributions, Scientific reports, Nature, Vol. 6(31536), pp. doi 10.1038/srep31536, 2016.