WH_MAT_DIST: L2 Wasserstein distance matrix

In Airpino/HistDAWass: Histogram-Valued Data Analysis

L2 Wasserstein distance matrix

Description

The function extracts the L2 Wasserstein distance matrix from a MatH object.

Usage

WH_MAT_DIST(x, simplify = FALSE, qua = 10, standardize = FALSE)

Arguments

x	A MatH object (a matrix of distributionH).
simplify	A logic value (default is FALSE), if TRUE histograms are recomputed in order to speed-up the algorithm.
qua	An integer, if simplify=TRUE is the number of quantiles used for recodify the histograms.
standardize	A logic value (default is FALSE). If TRUE, histogram-valued data are standardized, variable by variable, using the Wasserstein based standard deviation. Use if one wants to have variables with std equal to one.

Value

A matrix of squared L2 distances.

References

Irpino A., Verde R. (2006). A new Wasserstein based distance for the hierarchical clustering of histogram symbolic data. In: Batanjeli et al. Data Science and Classification, IFCS 2006. p. 185-192, BERLIN:Springer, ISBN: 3-540-34415-2

Examples

DMAT <- WH_MAT_DIST(x = BLOOD, simplify = TRUE)

Airpino/HistDAWass documentation built on Jan. 30, 2024, 7:53 p.m.