estimateDensity2D {DataVisualizations} | R Documentation |
estimateDensity2D
Description
Estimates densities for two-dimensional data with the given estimation type
Usage
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.
Value
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 |
Author(s)
Luca Brinkman and Michael Thrun
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
Examples
X=runif(100)
Y=rnorm(100)
#V=estimateDensity2D(X,Y)