CStats:GetStatus CStats:MaxClipMean

CStats:Kurtosis


The Kurtosis method computes the statistical skewness. Kurtosis measures the "peakiness" (or flatness) of the distribution of values in the sample.

The return value is adjusted to a reference value of 0 for the Normal ("Gaussian") distribution. A kurtosis value greater than 0 indicates that the distribution is taller than a Normal distribution (too narrow, or "leptokurtic"). Conversely, a kurtosis value less than 0 indicates the distribution is flatter than a Normal distribution (too flat, or "platykurtic"). By definition, the Normal distribution has the reference ratio of central area to tail area adjusted to 0, and is called "mesokurtic".

Syntax

nKurtosis = CStats:Kurtosis( CImage, CRect )

nKurtosis = CStats:Kurtosis( CImage )

nKurtosis = CStats:Kurtosis( table )

bullet.gif    CRect is a bounding rectangle for the CImage object.

bullet.gif    table is a 1-dimensional array containing numbers.

bullet.gif    On success, returns the skewness.

bullet.gif    On failure, returns 0.

Example

Suppose a CImage named I and a CRect named R exist. The following script returns the skewness inside a rectangle on the image:

S = new_stats()

-- create a CStats object

-- specify CImage and CRect to measure

 

nVal = S:Kurtosis(I, R)

-- returns the skewness

Printf("Kurtosis=%lg\n", nVal)

-- list the results

S:delete()

-- when done with S, remove it from memory

Related Topics

CStats class, Mean, Skewness, CImage class, CRect class


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