[R] Discover significant change in sorted vector

[Gabor Grothendieck]

Try this:

> a <- c(2,3,3,5,6,8,8,9,15, 25, 34,36,36,38,41,43,44,44,46);
> ix <- seq_along(a)
> library(strucchange)
> bp <- breakpoints(a ~ ix, h = 4)
> bp

         Optimal 3-segment partition:

Call:
breakpoints.formula(formula = a ~ ix, h = 4)

Breakpoints at observation number:
7 11

Corresponding to breakdates:
0.3684211 0.5789474
> plot(a ~ ix)
> lines(ix, fitted(bp))


On Wed, Apr 22, 2009 at 7:27 AM, Hans-Henning Gabriel
<hanshenning.gabriel at gmail.com> wrote:
> Hi,
>
> suppose I have a simple sorted vector like this:
>
> a <- c(2,3,3,5,6,8,8,9,15, 25, 34,36,36,38,41,43,44,44,46);
>
> Is there a function in R, I can use to discover that from index 8 to index
> 11 the values are changing significantly?
> The function should return a value pointing to one of the indices 8, 9, 10
> or 11. Any of them would be fine.
> The difficulty is that there may be no big gap. I mean, indices 8 and 11 are
> somehow "connected" by indices 9 and 10. So, it's not an option to just
> search for biggest difference between the values.
>
> Perfect would be a function that is able to discover multiple changes if it
> is present in the data.
>
> Thanks!!
> Henning
>
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