Re: size correction discriminant functions analyses

G'day Dr. Kidd, I've just started using a new computer and I put the wrong email address on my signature. The one below is the correct address. Did you have some comments about my last posting? see ya, Brett * Brett Human Shark Researcher 27 Southern Ave West Beach

RE: size correction discriminant functions analyses

-Original Message- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Sent: Wednesday, May 26, 2004 1:08 AM To: [EMAIL PROTECTED] Subject: Re: size correction discriminant functions analyses G'day all, Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL PROTECTED] Thanks

Re: size correction discriminant functions analyses

G'day all, Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL PROTECTED] Thanks to everyone for your comments. They've been a great help, and I'm glad that my question sparked a bit of discussion on the subject. After some pondering, I've got a few more questions and some more details

RE: size correction discriminant functions analyses

: size correction discriminant functions analyses G'day all, Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL PROTECTED] Thanks to everyone for your comments. They've been a great help, and I'm glad that my question sparked a bit of discussion on the subject. After some pondering, I've

Re: size correction discriminant functions analyses

1) PCA makes no assumptions about the distribution (multivariate normal or otherwise) of your data. It is a procedure that simply produces the linear combinations of variables with maximum variance subject to orthogonality to other such axes. OK, but variance may or may not be a meaningful

Re: size correction discriminant functions analyses

PROTECTED] Subject: Re: size correction discriminant functions analyses Dear collegues, Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL PROTECTED] About the above discussion on the linear measurements data for multivariate analysis, I should state that most times my problem (and I

Re: size correction discriminant functions analyses

Professor Geology Department Faculty of Science Minia University Egypt [EMAIL PROTECTED] http://myprofile.cos.com/aelewa - Original Message - From: [EMAIL PROTECTED] To: [EMAIL PROTECTED] Sent: Wednesday, May 19, 2004 04:29 ? Subject: Re: size correction discriminant functions analyses Just

Re: size correction discriminant functions analyses

Don't know what happened to cause the earlier message largely void of content, but I think the original communication was to correct the Red Book reference. The date is 1985, not 1982. -ds On Tue, 2004-05-18 at 14:12, [EMAIL PROTECTED] wrote: -- Dennis E. Slice, Ph.D. Department of

Re: size correction discriminant functions analyses

Dear collegues, Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL PROTECTED] About the above discussion on the linear measurements data for multivariate analysis, I should state that most times my problem (and I expect the problem of many people that wrks with it) is not of

Re: size correction discriminant functions analyses

correction discriminant functions analyses Just a comment on this one, from a pragmatic point of view. It is of course true that PCA is only *guaranteed* to produce components maximizing variance if you have multivariate normality. The theory of PCA is based on this assumption. But in many cases

Re: size correction discriminant functions analyses

Dr. Hammer, Please consider your courage credited. -ds A couple of points about PCA in general: 1) PCA makes no assumptions about the distribution (multivariate normal or otherwise) of your data. It is a procedure that simply produces the linear combinations of variables with maximum variance

Re: size correction discriminant functions analyses

Dear Brett, If the problem is separating size and shape, then, fortunately, in my edited book titled Morphometrics- Applications in Biology and Paleontology (Springer-Verlag, 2004) you will find a chapter that is written by Garcia-Rodriguez et al. They used the Sheared PCA analysis and could

Re: size correction discriminant functions analyses

. Cheers, Igor - Original Message - From: [EMAIL PROTECTED] To: [EMAIL PROTECTED] Sent: Tuesday, May 18, 2004 10:09 PM Subject: Re: size correction discriminant functions analyses Dear Brett and Marta, I think the problem you are encountering may not be the size-versus-shape issue

Re: size correction discriminant functions analyses

Just a comment on this one, from a pragmatic point of view. It is of course true that PCA is only *guaranteed* to produce components maximizing variance if you have multivariate normality. The theory of PCA is based on this assumption. But in many cases, PCA is used purely as a visualization

Re: size correction discriminant functions analyses

Useful, though sometimes technical, information, critiques, and expositions on the traditional use of ratios in morphometric analysis can be found in: Bookstein, F. L. 1991. Morphometric Tools for Landmark Data: Geometry and Biology. (The Orange Book) and Bookstein, F. L., Chernoff, B., Elder,

Re: size correction discriminant functions analyses

PROTECTED] Subject: Re: size correction discriminant functions analyses Brett: Darroch and Mosimann (1985) is a frequently-cited paper that talks about scale adjustment for both PCA and CVA. They use log-shape data that are ln-transformed ratios. That paper should be a useful starting

Re: size correction discriminant functions analyses

You mention that you have many more variables than specimens. As a result, you cannot use the various alternatives that you list. Discriminant functions, canonical variates, etc. all require that the pooled within-group covariance matrix be based on a sample size larger than the number of

Re: size correction discriminant functions analyses

PROTECTED] Sent: Tuesday, May 18, 2004 9:50 AM To: [EMAIL PROTECTED] Subject: Re: size correction discriminant functions analyses Dear Brett, I have the same problem. I found several approaches in the literature, bbut non efficient or clear review... well there were some, but too mathematic

Re: size correction discriminant functions analyses

-- Dennis E. Slice, Ph.D. Department of Biomedical Engineering Division of Radiologic Sciences Wake Forest University School of Medicine Winston-Salem, North Carolina, USA 27157-1022 Phone: 336-716-5384 Fax: 336-716-2870 Sender: [EMAIL PROTECTED] Precedence: bulk Reply-To: [EMAIL