HexaQerrsQuant: Realtive quantization error distribution on the SOM map

In SOMEnv: SOM Algorithm for the Analysis of Multivariate Environmental Data

Description

Plot a SOM map with realtive quantization error plotted as grayscale according to quartiles

Usage

HexaQerrsQuant(bmus, qerrs, Coord, Row, Col)

Arguments

bmus	Vector with Best Matching Unit for each experimental sample
qerrs	Vector with quantization error for each experimental sample
Coord	Prototype coordinates for plotting the map
Row	Number of SOM map rows
Col	Number of SOM map columns

Details

The function evaluate the relative quantization error for each prototype dividing the sum of quantization errors for experimental sample represented by the single prototype by the number of hits of the same prototype, then plots a SOM map with the realtive quantization error represented as grayscale according to quartiles, from white (lower outliers) followed by grayscale (quartiles) and black (upper outiliers). The outilers and quartiles are evaluated by boxplot function applying default parameters.

Value

Plot a SOM map with realtive quantization error represented as grayscale according to quartiles

Author(s)

S. Licen

References

Licen, S., Cozzutto, S., Barbieri, P. (2020) Aerosol Air Qual. Res., 20 (4), pp. 800-809. DOI: 10.4209/aaqr.2019.08.0414

See Also

boxplot

SOMEnv documentation built on July 26, 2021, 5:06 p.m.