Note: This page has been translated by MathWorks. Please click here

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

To view all translated materals including this page, select Japan from the country navigator on the bottom of this page.

Find outliers in data

`TF = isoutlier(A)`

`TF = isoutlier(A,method)`

`TF = isoutlier(A,movmethod,window)`

`TF = isoutlier(___,dim)`

`TF = isoutlier(___,Name,Value)`

```
[TF,lower,upper,center]
= isoutlier(___)
```

returns
a logical array whose elements are `TF`

= isoutlier(`A`

)`true`

when an
outlier is detected in the corresponding element of `A`

.
By default, an outlier is a value that is more than three scaled median absolute
deviations (MAD) away from the median. If `A`

is
a matrix or table, then `isoutlier`

operates on each
column separately. If `A`

is a multidimensional array,
then `isoutlier`

operates along the first dimension
whose size does not equal 1.

specifies
a moving method for determining local outliers according to a window
length defined by `TF`

= isoutlier(`A`

,`movmethod`

,`window`

)`window`

. For example, `isoutlier(A,'movmedian',5)`

returns `true`

for
all elements more than three local scaled MAD from the local median
within a sliding window containing five elements.

specifies
additional parameters for detecting outliers using one or more name-value
pair arguments. For example, `TF`

= isoutlier(___,`Name,Value`

)`isoutlier(A,'SamplePoints',t)`

detects
outliers in `A`

relative to the corresponding elements
of a time vector `t`

.

Was this topic helpful?