# rmoutliers

Detect and remove outliers in data

## Syntax

## Description

detects and removes outliers from the data in `B`

= rmoutliers(`A`

)`A`

.

If

`A`

is a row or column vector,`rmoutliers`

detects outliers and removes them.If

`A`

is a multidimensional array, then`rmoutliers`

operates along the first dimension of`A`

whose size does not equal 1.If

`A`

is a matrix,`rmoutliers`

detects outliers in each column of`A`

separately and removes the entire row.If

`A`

is a table or timetable,`rmoutliers`

detects outliers in each 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) away from the median.

specifies additional parameters for detecting and removing outliers using one or more
name-value 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`

.

## Examples

## Input Arguments

## Output Arguments

## Extended Capabilities

## Version History

**Introduced in R2018b**