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Detect and remove outliers in data

`B = rmoutliers(A)`

`B = rmoutliers(A,method)`

`B = rmoutliers(A,'percentiles',threshold)`

`B = rmoutliers(A,movmethod,window)`

`B = rmoutliers(___,dim)`

`B = rmoutliers(___,Name,Value)`

```
[B,TF] =
rmoutliers(___)
```

detects and removes outliers from the data in a vector, matrix, table, or timetable. `B`

= rmoutliers(`A`

)

If

`A`

is a row or column vector,`rmoutliers`

detects outliers and removes them.If

`A`

is a matrix, table, or timetable,`rmoutliers`

detects outliers in each column or variable of`A`

separately and removes the entire row.

By default, an outlier is a value that is more than three scaled median absolute deviations (MAD).

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

= rmoutliers(___,`Name,Value`

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

detects outliers in `A`

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

.

`fillmissing`

| `filloutliers`

| `ismissing`

| `isoutlier`

| `rmmissing`