# smooth

Smooth response data

## Syntax

## Description

smooths
the response data in column vector `yy`

= smooth(`y`

)`y`

using a moving average
filter.

The first few elements of `yy`

follow.

yy(1) = y(1) yy(2) = (y(1) + y(2) + y(3))/3 yy(3) = (y(1) + y(2) + y(3) + y(4) + y(5))/5 yy(4) = (y(2) + y(3) + y(4) + y(5) + y(6))/5 ...

`smooth`

handles endpoints, the result differs from the result
returned by the `filter`

function.

performs the operation on a GPU using `gpuarrayYY`

= smooth(`gpuarrayY`

,___)`gpuArray`

data. You can use
`gpuArray`

response data with all previous syntaxes. This syntax
requires Parallel Computing Toolbox™.

performs the operation on a GPU using `gpuarrayYY`

= smooth(`gpuarrayX`

,`gpuarrayY`

,___)`gpuArray`

input data. This syntax
requires Parallel Computing Toolbox.

**Note**

Using `gpuArray`

`x`

and `y`

inputs with the `smooth`

function is only recommended if you use the default method, `'moving'`

.
Using GPU data with other methods does not offer any performance advantage.

## Examples

## Input Arguments

## Output Arguments

## Tips

You can generate a smooth fit to your data using a smoothing spline. For more information, see

`fit`

.

## Alternative Functionality

You can also smooth data by using the MATLAB^{®}
`smoothdata`

function. With the exception of GPU array support, `smoothdata`

includes all the functionality of the
`smooth`

function and has some advantages. Unlike
`smooth`

, the `smoothdata`

function supports:

Matrices, tables, and timetables

Moving median and Gaussian methods

Option to specify how the

`NaN`

values are treatedOption to substitute smoothed data for the original matrix or append smoothed data to the original matrix

Tall arrays, C/C++ code generation, and thread-based environments

## Extended Capabilities

## Version History

**Introduced before R2006a**