R: ParetoRadius for distributions

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

[Package DataVisualizations version 1.2.3 Index]