R help - Jan 2010 - time series analysis for a time series without a regular frequency

Hello,

I am trying to conduct a time series analysis on historic hydrologic data,
but I cannot coerce it into class ts because it does not have regular
sampling intervals (some years have 20 samples, other have 8). Specifically
I am trying to perform a CUSUM or or other step change detection, but the
packages all seem to require data as ts.

Is there a way to coerce my data into ts while maintaining all of my
samples?

Or alternatively, can someone recommend a package that does not require data
as ts?

Thanks!



-- 
Erin Hestir
Center for Spatial Technology and Remote Sensing
University of California Davis

	[[alternative HTML version deleted]]

The zoo package supports irregularly spaced time series and if your
create a zoo object z from your data then tt <- as.ts(z) will give you
a ts object, tt.  Since a ts object must be regularly spaced this will
add NAs to ensure that it is.

On Fri, Jan 8, 2010 at 3:05 PM, Erin Hestir <elhestir at ucdavis.edu>
wrote:
> Hello,
>
> I am trying to conduct a time series analysis on historic hydrologic data,
> but I cannot coerce it into class ts because it does not have regular
> sampling intervals (some years have 20 samples, other have 8). Specifically
> I am trying to perform a CUSUM or or other step change detection, but the
> packages all seem to require data as ts.
>
> Is there a way to coerce my data into ts while maintaining all of my
> samples?
>
> Or alternatively, can someone recommend a package that does not require
data
> as ts?
>
> Thanks!
>
>
>
> --
> Erin Hestir
> Center for Spatial Technology and Remote Sensing
> University of California Davis
>
> ? ? ? ?[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>

On Fri, 8 Jan 2010, Erin Hestir wrote:
> I am trying to conduct a time series analysis on historic hydrologic data,
> but I cannot coerce it into class ts because it does not have regular
> sampling intervals (some years have 20 samples, other have 8). Specifically
> I am trying to perform a CUSUM or or other step change detection, but the
> packages all seem to require data as ts.
As Gabor already pointed out: the zoo package can be used to store such 
data.

If you want to use the strucchange package for detecting changes then you 
can do two things:
   -  use a plain data.frame (without ts or some other time
      series class) which can be easily produced via
      as.data.frame(zoo_obj).
      Then the axis annotation in graphics won't be the time axis but
      the standard unit interval (= proportion of data). This is not so
      pretty but all statistical interpretations are still correct.
   - If zoo_obj is just a univariate series and you want to conduct a
     CUSUM test for a change in the mean you can do
       cus <- gefp(zoo_obj ~ 1)
       plot(cus)
       plot(cus, functional = meanL2BB)
     and so on. gefp() is the only function in strucchange that
     automatically supports "zoo".

hth,
Z
> Is there a way to coerce my data into ts while maintaining all of my
> samples?
>
> Or alternatively, can someone recommend a package that does not require
data
> as ts?
>
> Thanks!
>
>
>
> -- 
> Erin Hestir
> Center for Spatial Technology and Remote Sensing
> University of California Davis
>
> 	[[alternative HTML version deleted]]
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
>