# Chris Beaumont's IDL Library

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# medabsdev.pro

## Routines

`result = medabsdev(data [, sigma=sigma] [, median=median] [, even=even])`

This function returns a data set's median absolute deviation from the median.

`test`

## topmedabsdev

Statistics

`result = medabsdev(data [, sigma=sigma] [, median=median] [, even=even])`

This function returns a data set's median absolute deviation from the median. That is, it returns median( |data - median(data) | ) It is a proxy for the standard deviation, but is more resistent against outliers.

### Return value

median( |data - median(data)| )

NOTE: For the gaussian distribution, medabsdev / sigma = inverseErf(0.5) * sqrt(2) = 0.67449

EXAMPLES: IDL> dist = randomn(seed, 50) IDL> outlier = 1d7 IDL> data = [dist, outlier] IDL> print, stdev(dist), stdev(data) 1.09757 1400280.1 IDL> print, medabsdev(dist), medabsdev(data) 0.597564 0.59756410

data in required

An array of data

### Keywords

sigma in optional

If set, divide the median absolute deviation by inverseErf(0.5) * sqrt(2). This scales the MAD to an approximation for sigma (assuming a Gaussian distribution)

median in optional

On output, holds the median of the data

even in optional

If set and data contains an even number of points, medians are computed as the average of the two middle numbers. The returned values may not be an element of the original data.

### Author information

History:

Aug 2009: Written by Chris Beaumont Sep 2009: Added /SIGMA keyword. cnb. Oct 2009: Added input checking. cnb. Oct 2010: Added median keyword. cnb. Jul 2012: Added /even keyword. Julio Castro

`test`

## File attributes

 Modifcation date: Thu Jul 26 15:20:33 2012 Lines: 82