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ATOMS : NaN-toolbox details
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A statistics and machine learning toolbox
(1821 downloads for this version - 65713 downloads for all versions)
A more recent valid version with binaries for Scilab 5.3 exists:
Holger Nahrstaedt
Owner Organization
TU Berlin / FG Regelungssysteme
Holger Nahrstaedt
Creation Date
January 21, 2011
Source created on
Scilab 5.3.x
Binaries available on
Scilab 5.3.x:
Windows 32-bit Windows 64-bit
Install command
--> atomsInstall("nan")
            This toolbox is meanly ported from the nan-toolbox for matlab/octave.

Please note that same functions has to be renamed as there are exists already
scilab functions with the same name.

Data Correlation and Covariance

Descriptive Statistics


statistical Visualization


hypothesis Tests


cluster Analysis

utility functions
Files (3)
[2.14 MB]
Source code archive

[3.15 MB]
Windows 32-bit binary for Scilab 5.3.x
Windows 32-bit
Automatically generated by the ATOMS compilation chain

[3.15 MB]
Windows 64-bit binary for Scilab 5.3.x
Windows 64-bit
Automatically generated by the ATOMS compilation chain

News (0)
Comments (4)     Leave a comment 
Comment -- January 24, 2011, 01:53:08 PM    

See the "Guidelines To Design a Module" :

especially the "Avoid function name conflicts" section.

Would you want to work on the Stixbox module, instead of writing a statistics toolbox on
own ? I could easily add you as a project developer on the Forge.

Best regards,

Michaël Baudin
Comment -- January 24, 2011, 02:04:17 PM    

How is the nan_std function different from Scilab's st_deviation function ?

What is the difference between nan_trimean and Scilab's trimmean ?

There are others :
 * nan_unique : Scilab/unique ?
 * nan_mean : Scilab/mean ?
 * nan_var : Scilab/variance ?
 * nan_histo : Scilab/histplot ?
 * prctile, percentile : Scilab/perctl ?
 * quantile : Stixbox/quantile ?

Best regards,

Michaël Baudin
Comment from Holger Nahrstaedt -- January 24, 2011, 02:07:06 PM    
The different is only, that the nan_* functions can handle nan values.

-->nan_mean([1 2 %nan])
 ans  =
-->mean([1 2 %nan])
 ans  =
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