Date: Tue, 31 Aug 2010 14:37:16 -0700 (PDT)
From: rtist
To: r-help@r-project.org
Subject: Re: [R] Detecting Growth Trends
Message-ID: <1283290636694-2402347.p...@n4.nabble.com>
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If the test rejects the null, then it has determined that the new
If the test rejects the null, then it has determined that the new set of
incoming data is no longer purely oscillatory in the mean reverting sense
(it is now unit root and exhibits growth). Unless I misinterpreted, the OP
wants to find a statistical method to determine such behavior beyond purely
Error of the 3rd kind, (right answer to wrong question), I think. So what if
the test rejects --- then what?
I think the poster is looking for some kind of smoother.
?loess, ?smooth.spline and about 400 others may be useful.
--
Bert Gunter
Genentech Nonclinical Statistics
On Tue, Aug 31, 2010 a
You can try a unit root test which test for stationarity in a series.
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R-help@r-pr
Dear All,
I am given some noisy data which (by naked eye) appears to be
oscillating first but finally growing.
Is there any statistical set (I mean something different from e.g. a
linear fit, which would not be convincing at all in my case) to detect
growth (possibly without relying on any data
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