-------- Original Message -------- Subject: Re: Prediction of landmark coordinates from other landmarks Date: Sat, 15 Jan 2011 02:59:26 -0500 From: Stefan Schlager <[email protected]> To: [email protected] 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]> To: [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!
