## ./

# detectoutlier.pro

## Routines

`detectoutlier_plot, x, y, result`

Plot which objects were flagged as outliers from detectoutlier.

`result = detectoutlier(x, y, status [, THRESH=THRESH] [, VERBOSE=VERBOSE] [, PLOT=PLOT])`

This function attempts to identify outlier data points in 2D space.

## Routine details

## topdetectoutlier_plot

Display utilities

`detectoutlier_plot, x, y, result`

Plot which objects were flagged as outliers from detectoutlier.

### Parameters

- x in required
Input x points

- y in required
Input y points

- result in required
A vector of [0,1] to denote [outlier/non-outlier]

## topdetectoutlier

statistics

`result = detectoutlier(x, y, status [, THRESH=THRESH] [, VERBOSE=VERBOSE] [, PLOT=PLOT])`

This function attempts to identify outlier data points in 2D space. It proceeds as follows: 1) Calculate the center position of all points 2) Remove the biggest outlier, and recalculate the center and standard deviation. 3) If the outlier removed in step 2 deviates from the new center by more than THRESH * stdev, go to step 1 and repeat. Otherwise, re-insert the outlier flagged in step 2 as a legitimate data point, and return.

### Parameters

- x
- y
- status

### Keywords

- THRESH in optional
Use to manually set the threshhold for outlier detection. The default is 3.5

- VERBOSE in optional
Output textual information

- PLOT in optional
Plot the points, color coded by whether they are outliers or not.

## File attributes

Modifcation date: | Mon Mar 22 16:17:13 2010 |

Lines: | 142 |