ParetoRadius {DataVisualizations} | R Documentation |
ParetoRadius for distributions
Description
Calculation of the ParetoRadius i.e. the 18 percentiles of all mutual Euclidian distances in data.
Usage
ParetoRadius(Data, maximumNrSamples = 10000,
plotDistancePercentiles = FALSE)
Arguments
Data |
numeric data vector |
maximumNrSamples |
Optional, numeric. Maximum number for which the distance calculation can be done. 1000 by default. |
plotDistancePercentiles |
Optional, logical. If TRUE, a plot of the percentiles of distances is produced. FALSE by default. |
Details
The Pareto-radius of the hyperspheres is derived from the optimization of information for minimal set size. ParetoRadius() is a kernel density estimation for variable intervals. It works only on Data without missing values (NA) or NaN. In other cases, please use ParetoDensityEstimation directly.
Value
numeric value, the Pareto radius.
Note
This the second version of the function prior available in AdaptGauss.
For larger datasets the quantile_c() function is used instead of quantile in R which was programmed by Dirk Eddelbuettel on Jun 6 and taken by the author from https://github.com/RcppCore/Rcpp/issues/967.
Author(s)
Michael Thrun
References
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, Proc Gfkl 2003, pp 91-100, Springer, Berlin, 2005.
See Also
ParetoDensityEstimation, OptimalNoBins