Description Usage Arguments Details Value Author(s) References Examples
The function determines a robust subsample utilizing self-organizing maps (SOM).
1 |
data |
At least a two-dimensional data matrix is required. Number of observations needs to be greater than number of dimensions. |
Nx |
Size of the SOM-net in x direction. Default is 10. |
Ny |
Size of the SOM-net in y direction. Default is 10. |
rlen |
Number of iterations during SOM learn process. Default is 2000. |
The function first calls the som
function within the som-package. The results are subsequently used to determine a robust subsample. Arguments Nx
, Ny
and rlen
are passed to som
. These arguments should be selected depending on the size of the data set (number of observations/dimensions). The larger the data set the larger the net size and the number of iterations should be. Note: At the moment only rectangular and quadratic SOM nets are supported.
som.results |
SOM results as delivered by |
som.neigh |
A matrix showing for every neuron (first column) the index off the neighboring neurons (columns 2-5). |
umatrix |
The U-matrix shows the U-value for every neuron. |
winneuron |
Vector of length |
lib |
List of all basins found. Index of neurons. Smallest subsample of size |
lin |
List of all neighboring neurons per basin. Index of neurons. Smallest subsample of size |
geb |
Number of associated data points per basin. Smallest subsample of size |
l |
Internal value necessary for plotting. |
fafh |
Data for plotting the flood area flood height curve. |
fafh.lib |
Internal data necessary for plotting extented flooding. |
fafh.drin |
Internal data necessary for plotting extented flooding. |
drin |
Robust subsample of minimal size. |
Steffen Liebscher <steffen.liebscher@wiwi.uni-halle.de>
Liebscher, S., Kirschstein, T., and Becker, C. (2012): The Flood Algorithm - A Multivariate, Self-Organizing-Map-Based, Robust Location and Covariance Estimator, Statistics and Computing, 22(1), 325-336, DOI: 10.1007/s11222-011-9250-3.
1 | # flood(halle)
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