DistanceDistributions {BIDistances} | R Documentation |
Distance Distribution
Description
Calculates the distribution of the distances between the data points
Usage
DistanceDistributions(Data, DistanceMethods=c('bhjattacharyya', 'bray',
'canberra', 'chord',
'divergence', 'euclidean',
'minkowski', 'geodesic',
'hellinger', 'kullback',
'manhattan', 'maximum',
'soergel', 'wave',
'whittaker'),
CosineNonParallel = TRUE, CorrelationDist = TRUE,
Mahalanobis = FALSE, Podani = FALSE,
PlotIt = FALSE, PlotSampleSize = 5e3)
Arguments
Data |
[1:n, 1:m] A matrix, containing data as rows. |
DistanceMethods |
Character vector stating all distance methods such as 'euclidean'. |
CosineNonParallel |
Boolean stating if cosine should be computed in parallel. |
CorrelationDist |
Boolean stating if CorrelationDist should be computed. |
Mahalanobis |
Boolean stating if Mahalanobis should be computed. |
Podani |
Boolean stating if Podani should be computed. |
PlotIt |
Boolean: TRUE => create plot. FALSE => no plot. |
PlotSampleSize |
Integer stating the number of samples for plotting. |
Value
List with elements
DistanceMatrix |
[1:n, 1:n] numeric matrix containing the distance matrix |
DistanceChoice |
[1:n, 1:n] numeric matrix containing the distance matrix |
OrderedDistances |
[1:n, 1:n] numeric matrix containing the distance matrix |
ggobject |
ggplot object |
Author(s)
Michael Thrun
Examples
iris=datasets::iris
if(requireNamespace("DataVisualizations",quietly=TRUE)){
library(DataVisualizations)
DistanceDistributions(as.matrix(iris[,1:4]), c("euclidean"), PlotIt = FALSE)
}
[Package BIDistances version 0.1.3 Index]