R help - Nov 2007 - Exponential Smoothing for ggplot2's stat_smooth()

Hello everyone,

I was wondering if anyone was aware of a way in which I could use ggplot's
stat_smooth() function for add an exponential moving average.

I was thinking that I could maybe use something like:
>myggplot + stat_smooth (method = 'HoltWinters( data , .9 , 0, 0)')
but my efforts were futile.

Perhaps there is a way to write my own custom method to throw into
stat_smooth??

Thanks,
- Mike

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Hi Michael,

To use stat_smooth as is, you need a smoothing function that basically
works like lm.  So you have two options: to make an interface to
HoltWinters (or find another exponential smooth that already has that
interface) or write your own stat object, which might look something
like this:

StatExpo <- proto(Stat, {
  objname <- "expo"
  desc <- "Exponential smoothing"
  default_geom <- function(.) GeomLine

  calculate_groups <- function(., data, scales, variable="x", ...)
{
    data$y <- HoltWinters(data$x, ...)
  }
})
stat_expo <- StatExpo$new

Then you could use myggplot + stat_expo(alpha = 0.9, beta = 0, gamma = 0)

Hadley


On 11/16/07, Michael King <wmichaelking1 at gmail.com>
wrote:
> Hello everyone,
>
> I was wondering if anyone was aware of a way in which I could use
ggplot's
> stat_smooth() function for add an exponential moving average.
>
> I was thinking that I could maybe use something like:
>
> >myggplot + stat_smooth (method = 'HoltWinters( data , .9 , 0,
0)')
>
> but my efforts were futile.
>
> Perhaps there is a way to write my own custom method to throw into
> stat_smooth??
>
> Thanks,
> - Mike
>
>         [[alternative HTML version deleted]]
>
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>

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