[R] Population abundance, change point
Jonathan P Daily
jdaily at usgs.gov
Wed Nov 24 16:59:17 CET 2010
I agree that SiZer is not the ultimate answer to all changepoint analysis,
but that is why there are so many changepoint detection methods used. I
will clarify, though, that my understanding of SiZer (which may be wrong)
was that the smoothing splines are just a vessel for finding the
changepoints, and made no assumptions about the continuity of the
changepoint itself.
One thing that would certainly help, especially with the confidence
intervals about 0, is some bandwidth selection standard, though choosing
that standard would be a difficult process to say the least.
--------------------------------------
Jonathan P. Daily
Technician - USGS Leetown Science Center
11649 Leetown Road
Kearneysville WV, 25430
(304) 724-4480
"Is the room still a room when its empty? Does the room,
the thing itself have purpose? Or do we, what's the word... imbue it."
- Jubal Early, Firefly
Gavin Simpson <gavin.simpson at ucl.ac.uk> wrote on 11/24/2010 09:15:55 AM:
> [image removed]
>
> Re: [R] Population abundance, change point
>
> Gavin Simpson
>
> to:
>
> Jonathan P Daily
>
> 11/24/2010 09:16 AM
>
> Cc:
>
> Mike Marchywka, r-help, r-help-bounces, carusonm
>
> Please respond to gavin.simpson
>
> On Wed, 2010-11-17 at 09:17 -0500, Jonathan P Daily wrote:
> > Indeed I have looked into various non-standard changepoint analysis
> > methods. I figured the OP was more interested in traditional methods
since
> > you have to spend less time justifying your methodology. Wavelets are
one
> > potential nontraditional method, as is Significant Zero Crossings (R
> > package SiZer), which fits arbitrary-degree smoothing splines over a
range
> > of bandwidth parameters and looks for changes.
>
> ...By looking to see if the derivative of the fitted curve is different
> from 0 (given a suitable confidence interval on the derivative. My
> problem with all of this is that these data are time series and SiZeR
> doesn't take this into account (AFAICS) when computing the confidence
> intervals - they are certainly too narrow for examples I have run.
>
> Also, if these things are using splines, aren't we already assuming that
> the underlying function is smooth and not a discontinuity? So which
> technique the OP chooses will depend on how they think about the type of
> change taking place at the "changepoint" - a point I think you made
> earlier Jonathan.
>
> Don't mean to be too negative, this has been a very useful discussion
> that I am coming to late after a spot of time in the field.
>
> All the best,
>
> G
>
> > With large communities of
> > abundance counts, another approach that is gaining popularity is the
> > community-level indicator taxa analysis (TITAN), though that is not
useful
> > to the OP.
> > --------------------------------------
> > Jonathan P. Daily
> > Technician - USGS Leetown Science Center
> > 11649 Leetown Road
> > Kearneysville WV, 25430
> > (304) 724-4480
> > "Is the room still a room when its empty? Does the room,
> > the thing itself have purpose? Or do we, what's the word... imbue
it."
> > - Jubal Early, Firefly
> >
> > Mike Marchywka <marchywka at hotmail.com> wrote on 11/17/2010 09:11:11
AM:
> >
> > > [image removed]
> > >
> > > RE: [R] Population abundance, change point
> > >
> > > Mike Marchywka
> > >
> > > to:
> > >
> > > jdaily, carusonm
> > >
> > > 11/17/2010 09:11 AM
> > >
> > > Cc:
> > >
> > > r-help, r-help-bounces
> > >
> > >
> > >
> > >
> > >
> > > > To: carusonm at gmail.com
> > > > From: jdaily at usgs.gov
> > > > Date: Wed, 17 Nov 2010 08:45:01 -0500
> > > > CC: r-help at r-project.org; r-help-bounces at r-project.org
> > > > Subject: Re: [R] Population abundance, change point
> > > >
> > > > There are really no set ways to determine a changepoint, since a
> > > > changepoint depends completely on what you decide. Recursive
> > partitioning
> > > > will fit a best changepoint, but it will pretty much always fit
one.
> > This
> > > If you are open to newer ideas,
> > > have you looked at wavelets at all? these come up on googel along
with
> > R.
> > > Also with aonly a few points, even 20-30, you coldconsider
exhasiutvely
> > > fitting slopes to all 2^n subsets and plowing throgh the histograms
> > > looking for anything that may be publishable or illuminating about
your
> > data.
> > > Fitting to your own model or null hypotheses would make interesting
> > > contrasts of course, " populations remained the same after atrazine
> > spill
> > > or asteroid hit" etc.
> > >
> > >
> > > > function can be found in the package rpart:
> > > >
> > > > > fit <- rpart(count ~ year, control = list(maxdepth = 1))
> > > > > summary(fit)
> > > >
> > > > However this measure offers no level of confidence. This is where
> > packages
> > > > like strucchange and party come into use, as they provide measures
of
> > > > confidence. Alternatively, you could look into regression-based
> > methods
> > > > where the changepoint is some parameter. Piecewise regression, for
> > > > instance, is as simple as fitting a spline of degree 1 and
changepoint
> > X:
> > > >
> > > > > library(splines)
> > > > > fit <- lm(count ~ bs(year, knots = X, degree = 1))
> > > > > plot(year, count)
> > > > > lines(year, fitted(fit))
> > > >
> > > > Then you can fit a regression at each year and compare.
Alternatively,
> > > > since count data is often noisy, you could easily substitute
quantile
> > > > regression for linear regression to much of the same effect
(assuming
> > > > whatever tau you decide, I used 0.8 but this is arbitrary):
> > > >
> > > > > library(splines)
> > > > > library(quantreg)
> > > > > fit <- rq(count ~ bs(year, knots = X, degree = 1), tau = 0.8)
> > > > > plot(year, count)
> > > > > lines(year, fitted(fit))
> > > > --------------------------------------
> > > > Jonathan P. Daily
> > > > Technician - USGS Leetown Science Center
> > > > 11649 Leetown Road
> > > > Kearneysville WV, 25430
> > > > (304) 724-4480
> > > > "Is the room still a room when its empty? Does the room,
> > > > the thing itself have purpose? Or do we, what's the word... imbue
it."
> > > > - Jubal Early, Firefly
> > > >
> > > > r-help-bounces at r-project.org wrote on 11/16/2010 05:30:49 PM:
> > > >
> > > > > [image removed]
> > > > >
> > > > > [R] Population abundance, change point
> > > > >
> > > > > Nicholas M. Caruso
> > > > >
> > > > > to:
> > > > >
> > > > > r-help
> > > > >
> > > > > 11/16/2010 05:32 PM
> > > > >
> > > > > Sent by:
> > > > >
> > > > > r-help-bounces at r-project.org
> > > > >
> > > > > I am trying to understand my population abundance data and am
> > looking
> > > > into
> > > > > analyses of change point to try and determine, at approximately
what
> > > > point
> > > > > do populations begin to change (either decline or increasing).
> > > > >
> > > > > Can anyone offer suggestions on ways to go about this?
> > > > >
> > > > > I have looked into bcp and strucchange packages but am not
> > completely
> > > > > convinced that these are appropriate for my data.
> > > > >
> > > > > Here is an example of what type of data I have
> > > > > Year of survey (continuous variable) 1960 - 2009 (there are gaps
in
> > the
> > > > > surveys (e.g., there were no surveys from 2002-2004)
> > > > > Relative abundance of salamanders during the survey periods
> > > > >
> > > > >
> > > > > Thanks for your help, Nick
> > > > >
> > > > > --
> > > > > Nicholas M Caruso
> > > > > Graduate Student
> > > > > CLFS-Biology
> > > > > 4219 Biology-Psychology Building
> > > > > University of Maryland, College Park, MD 20742-5815
> > > > >
> > > > >
> > > > >
> > > > >
> > > > >
------------------------------------------------------------------
> > > > > I learned something of myself in the woods today,
> > > > > and walked out pleased for having made the acquaintance.
> > > > >
> > > > > [[alternative HTML version deleted]]
> > > > >
> > > > > ______________________________________________
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> > > > R-help at r-project.org mailing list
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> > > > PLEASE do read the posting guide
> > http://www.R-project.org/posting-guide.html
> > > > and provide commented, minimal, self-contained, reproducible code.
> > >
> >
> > ______________________________________________
> > 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.
>
> --
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> Dr. Gavin Simpson [t] +44 (0)20 7679 0522
> ECRC, UCL Geography, [f] +44 (0)20 7679 0565
> Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk
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