The NaN-toolbox: A statistics and machine learning toolbox for Octave and
for data with and w/o MISSING VALUES encoded as NaN's.
FEATURES of the NaN-toolbox:
- Statistical tools
- classification methods (including FDA/LDA, MDA/QDA, NBC/aNBC, REG/PLS, WienerHopf, PLA, SVM ...)
- NaN`s are treated as missing values
- supports weighting of data samples
- yields more often the correct result (instead of NaN)
- less but more powerful functions (no nan-FUN needed)
- fixes known bugs of traditional functions
- compatible to Matlab and Octave
- significance test, confidence intervals and Spearman`s rank correlation included in CORRCOEF
- CORRCOEF checks whether NaN's (missing values) are correlated with data
- flexible control of granularity for explicit checks of NaN's
- NEW: parallel execution on multicore platforms 
For more information see also:
More information on NaN's is available at:
Wiki (Octave) ,
If you find this toolbox useful, and you want it to be part of Octave or Matlab, send me an e-mail.
An e-mail to the maintainer of Octave or one of the
Octave-mailinglists might also help.
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