Method ao/detectOutliers
DETECTOUTLIERS locates outliers in data.
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DESCRIPTION: DETECTOUTLIERS locates outliers in ao objects.
CALL: out = obj.detectOutliers(pl)
out = detectOutliers(objs, pl)
INPUTS: pl - parameter list containing detection threshold
obj(s) - input ao object(s)
OUTPUTS: out - timeseries aos (one per input ao) corresponding to a
flag for detected outliers (1 for outlier, 0 for normal data)
Parameters Description
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| Method Details |
|
| Access |
public |
| Defining Class |
ao |
| Sealed |
0 |
| Static |
0 |
Parameter Description
| Sets for this method … |
|---|
| Default |
Default |
| no description |
| Key |
Default Value |
Options |
Description |
| detectOutliers |
| THRESHOLD |
10 |
none |
Trigger threshold for detecting outliers. For Gaussian white noise with infrequent outliers, the units correspond to standard deviations. |
| CUSHION |
[] |
none |
Number of data points to include before outlier trigger start and after outlier trigger end. Effectively widens triggered area. Can either specify a single value or a 2-element array corresponding to pre- and post-trigger cushion. |
Example |
| plist('THRESHOLD', [10], 'CUSHION', [[]]) |
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| Some information of the method ao/detectOutliers are listed below: |
| Class name |
ao |
| Method name |
detectOutliers |
| Category |
Signal Processing |
| Package name |
ltpda |
| VCS Version |
967b0eec0dece803a81af8ef54ad2f8c784b20b2 |
| Min input args |
1 |
| Max input args |
-1 |
| Min output args |
1 |
| Max output args |
-1 |
| Can be used as modifier |
1 |
| Supported numeric types |
{'double'} |
 |
Method: ao/delayEstimate |
|
Method: ao/detrend |
 |
©LTP Team