Re: [MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-31 Thread Miguel Eduardo Delgado Burbano
*To:* f.james.ro...@stonybrook.edu > *Cc:* Elahep <ellie.parv...@gmail.com>; MORPHMET < > morphmet@morphometrics.org>; jkunk...@une.edu > > *Subject:* Re: [MORPHMET] Mahalanobis distance in cluster analysis of > shape variables > > > > Usually researchers use small

Re: [MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-31 Thread Miguel Eduardo Delgado Burbano
ail.com] > *Sent:* Saturday, January 30, 2016 7:14 AM > *To:* MORPHMET <morphmet@morphometrics.org> > *Cc:* ellie.parv...@gmail.com; jkunk...@une.edu > *Subject:* Re: [MORPHMET] Mahalanobis distance in cluster analysis of > shape variables > > > > Dear Joseph, >

RE: [MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-30 Thread F. James Rohlf
tion Research Professor, Anthropology Stony Brook University From: Elahep [mailto:ellie.parv...@gmail.com] Sent: Saturday, January 30, 2016 7:14 AM To: MORPHMET <morphmet@morphometrics.org> Cc: ellie.parv...@gmail.com; jkunk...@une.edu Subject: Re: [MORPHMET] Mahalanobis distance in cluste

Re: [MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-30 Thread Elahep
Dear Joseph, Thanks for your detailed explanation. As it is recommended by Claude in "morphometrics with R" (2008) it's better to use the Mahalanobis distance for clustering group means, because this will be scaled by the within-group variance-covariance. In my analysis, I calculated the mean

Re: [MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-30 Thread Joseph Kunkel
I can not speak directly to why it is frequently used in GM cluster analysis but I would like to mention how I look at Mahalanobis distance based on its calculation. Mahalanobis distance is not a pure distance metric like Euclidian or Manhattan distance, as you have stated it is

[MORPHMET] Mahalanobis distance in cluster analysis of shape variables

2016-01-30 Thread Elahep
Hello all, I have seen in many GM articles people use Mahalanobis distance for cluster analysis. What is the advantage of using Mahalanobis distance over Euclidian distance as similarity measure in cluster analysis of shape variables? As far as I know Mahalanobis distance is the