estimateDensity2D function

estimateDensity2D

Estimates densities for two-dimensional data with the given estimation type

estimateDensity2D(X, Y, DensityEstimation = "SDH",

SampleSize, na.rm = FALSE, NoBinsOrPareto = NULL)

Arguments

• X: [1:n] numerical vector of first feature
• Y: [1:n] numerical vector of second feature
• DensityEstimation: Either "PDE","SDH" or "kde2d"
• SampleSize: Sample Size in case of big data
• na.rm: Function may not work with non finite values. If these cases should be automatically removed, set parameter TRUE
• NoBinsOrPareto: Density specifc parameters, for PDEscatter(ParetoRadius) or SDH (nbins)) or kde2d(bins)

Details

Each two-dimensional data point is defined by its corresponding X and Y value.

Returns

List V with - X: [1:m] numerical vector of first feature, m<=n depending if all values are finite an na.rm parameter

• Y: [1:m] numerical vector of second feature, m<=n depending if all values are finite an na.rm parameter

• Densities: the density of each two-dimensional data point

References

[Ultsch, 2005] Ultsch, A.: Pareto density estimation: A density estimation for knowledge discovery, In Baier, D. & Werrnecke, K. D. (Eds.), Innovations in classification, data science, and information systems, (Vol. 27, pp. 91-100), Berlin, Germany, Springer, 2005.

[Eilers/Goeman, 2004] Eilers, P. H., & Goeman, J. J.: Enhancing scatterplots with smoothed densities, Bioinformatics, Vol. 20(5), pp. 623-628. 2004

Author(s)

Luca Brinkman and Michael Thrun

Examples

X=runif(100)
Y=rnorm(100)
#V=estimateDensity2D(X,Y)