-------- Original Message --------
Subject:        tpsReg permutation test problem
Date:   Tue, 18 Jan 2011 14:00:16 -0500
From:   Francisco prevosti <[email protected]>
To:     [email protected]



Hi everybody,

My dataset is 99 specimen per 42 landmarks (the aligment specimen files)
and the centroid size file.

I have a problem when I try to run the permutation test of tpsReg using
"Permute All" and default settings. I got this message: Invalid Floating
Point Operation.

I tried with different windows version and tpsReg versions (1.37 for
example).

I got other result in ok conditions (regression report even the
Generalized Goodal F test; visualization of shape change along
regression.. etc).

May be someone can help me to do this test.

Sincerely,


pancho
Francisco J. Prevosti
División Mastozoología
Museo Argentino de Ciencias Naturales "Bernardino Rivadavia" - CONICET
Av. Angel Gallardo 470 - C1405DJR -
Buenos Aires - Argentina -
Tel/Fax.: (5411) 4982-0306 / 1154 / 5243 / 4494 - Int. 210
http://www.macn.secyt.gov.ar/

--- On *Tue, 1/18/11, morphmet /<[email protected]>/*
wrote:


    From: morphmet <[email protected]>
    Subject: Re: Prediction of landmark coordinates from other landmarks
    To: "morphmet" <[email protected]>
    Date: Tuesday, January 18, 2011, 2:23 PM



    -------- Original Message --------
    Subject: Re: Prediction of landmark coordinates from other landmarks
    Date: Mon, 17 Jan 2011 02:13:43 -0500
    From: Pierre Guyomarc'h <[email protected]
    </mc/[email protected]>>
    To: [email protected]
    </mc/[email protected]>



    Thank you Stefan! I didn't think about that, I'll try and compare
    errors. I still would prefer a prediction method as my reference sample
    is not representative of ALL the existing shapes; and as the skull
    correlates (moderately ok...) with the skin, prediction may be more
    objective and less sample-specific. But the error rates may be better,
    I'll keep you posted about that!

    -- Pierre Guyomarc'h (PhD student)
    Université Bordeaux 1 - UMR 5199 PACEA (CNRS)
    /Anthropologie des Populations Passées et Présentes/ (A3P)
    Av. des Facultés, Bât B8 - 33405 Talence cedex


    On Sat, Jan 15, 2011 at 8:59 AM, Stefan Schlager
    <[email protected]
    </mc/[email protected]>
    <mailto:[email protected]
    </mc/[email protected]>>> wrote:

    Hi Pierre,
    you can use a nearestest neighbour method by generating a weighted
    (by Procrustes or Mahalanobisdistance) mean of the nearest
    neighbours - this avoids improbable prediction results. It works
    pretty good on facial estimation.

    If you are interested in R scripts, drop me aline or two.

    stefan

    --
    Stefan Schlager M.A.
    Anthropologie
    Medizinische Fakultät der der Albert Ludwigs- Universität Freiburg
    Hebelstr. 29
    79104 Freiburg

    Anthropology
    Faculty of Medicine, Albert-Ludwigs-University Freiburg
    Hebelstr. 29
    D- 79104 Freiburg

    phone +49 (0)761 203-5522
    fax +49 (0)761 203-6898



    On 14.01.2011 21:11, morphmet wrote:



    -------- Original Message --------
    Subject: Prediction of landmark coordinates from other landmarks
    Date: Fri, 14 Jan 2011 12:30:21 -0500
    From: Pierre Guyomarc'h <[email protected]
    </mc/[email protected]>
    <mailto:[email protected]
    </mc/[email protected]>>>
    To: [email protected]
    </mc/[email protected]>
    <mailto:[email protected]
    </mc/[email protected]>>



    Dear morphometricians,

    I’m trying to use geometric morphometrics to predict the
    coordinates of
    a group of landmarks from another group of landmarks (of the same
    individual). The goal is to predict human facial skin features
    from bony
    morphology. As I’m no mathematician or statistician, I have some
    difficulties to evaluate the integrity of my methods. After short
    discussion with some morphometricians, I heard different
    opinions and
    advices. That’s why I’m submitting my questions more largely by
    throwing
    this bottle to the sea! What do you think of:

    -Method 1: predict each 3D coordinate of the unknown landmarks
    (group 2)
    from the PCs of a PCA ran on the known landmarks (group 1) through
    multivariate regressions.

    -Method 2: use best covariating groups of landmarks through PLS
    analysis
    and use the scores and PCA to predict the 3D coordinates of group 2.
    This methodology has been proposed at the 4th Meeting of Junior
    Scientists in Anthropology (Freiburg im Breisgau, March 2010). The
    proceedings are available at
    http://www.freidok.uni-freiburg.de/volltexte/7603/ and my
    contribution
    is at p.84. Feel free to consult it if you have time. A more
    complete
    description of this method is exposed.

    -Method 3: I would be really grateful if you can find me a third
    method!

    I’m open to all comments, even negative ones since they are
    constructive…

    Thanks!





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