[R] time-series trend classification

[Bert Gunter]

If I understand you correctly, 5-10 points is not near enough to fit
anything beyond a simple linear trend unless you know a priori what
the form of the "trend" is. Period.

Admitting that the data are insufficient  is better than performing
misleading analyses. *

Cheers,
Bert

* My personal view. Others may disagree and offer more useful ways forward.

On Sun, Feb 19, 2012 at 2:25 PM, Roy Mendelssohn
<roy.mendelssohn at noaa.gov> wrote:
>
> On Feb 19, 2012, at 9:46 AM, John Kohr wrote:
>
>>
>> Hello everyone,
>>
>> I was looking for a way to classify time-series based on the curve-fit. I try to campute several trends so i was thinking to link each trend with a function. increase with exponential for example, increase and decrease with a gaussian etc. The possiblities are endless though and it seems that is not always working well, especially if you work on small time-series (of 5-10 points only - one point in the end of the time-series can make the nls function to not be able to find the best fit among all these functions). Is there any package doing something similar? or another technique that could capture such trends? I can't find any code or publication on that, so I guess is something that is tested and is not working?
>>
>> Any help is appreciated.
>>
>> Best,
>> John
>
> One option you have is to use StructTS  which fits what is essentially a non-parametric trend  (it is actually a local smooth of the data).  That should give you an idea of the time trend if you then prefer a functional form for the trend.  There are other packages that do similar analysis, StructTS is built into the basic stat package.
>
> HTH,
>
> -Roy M
>
>
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-- 

Bert Gunter
Genentech Nonclinical Biostatistics

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