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Find outliers in data

`TF = isoutlier(A)`

`TF = isoutlier(A,method)`

`TF = isoutlier(A,'percentiles',threshold)`

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

`TF = isoutlier(___,dim)`

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

```
[TF,L,U,C]
= 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 detecting 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`

.

`filloutliers`

| `ischange`

| `islocalmax`

| `islocalmin`

| `ismissing`

| `rmoutliers`