Karolin,

A reading of Rohlf 1999 may help.

Dean

Rohlf, F.J. 1999. Shape statistics: Procrustes superimpositions and tangent 
spaces. Journal of Classification. 16:197-223.

Dr. Dean C. Adams
Distinguished Professor of Evolutionary Biology
Director of Graduate Education, EEB Program
Department of Ecology, Evolution, and Organismal Biology
Iowa State University
https://faculty.sites.iastate.edu/dcadams/
phone: 515-294-3834

From: morphmet2@googlegroups.com <morphmet2@googlegroups.com> On Behalf Of 
karolin....@gmail.com
Sent: Tuesday, September 7, 2021 7:04 AM
To: Morphmet <morphmet2@googlegroups.com>
Subject: [MORPHMET2] Questions about Kendall’s shape space and tangent space 
projection

Dear Morphometricians,

I am currently trying to understand the mathematical backgrounds of 
landmark-based geometric morphometrics. Some questions arose that we could not 
answer during discussions in our lab which is why I hope you can help - many 
thanks in advance!

The first question is: What exactly is “Kendall’s shape space”? If I understand 
Kendall’s (1984) statement in Eq. 4 correctly, the shape space is a quotient 
space; the elements are equivalence classes of pre-shapes (a fiber on the 
pre-shape sphere becomes one element in shape space). The elements of the 
equivalence classes have less “coordinates” (vector elements) than the original 
landmark configuration and lie on a hyperdimensional sphere with a radius of 1. 
In Theorem 2 Kendall (1984) states that the shape space for triangles is 
isometric to a three-dimensional sphere with a radius of 0.5. The triangles on 
this sphere with a radius of 0.5 are represented by three Cartesian coordinates 
that are calculated from the original landmark configuration (Kendall 1984, 
section 5), whereas the triangles are represented by equivalence classes in 
shape space.
In several publications I now find illustrations of a hemisphere of radius 1 
and a sphere of radius 0.5 (both share one point at the pole); those 
publications usually use the full landmark set. The sphere of radius 0.5 is 
often termed “Kendall’s shape space” (sometimes with a reference to triangles, 
sometimes not). So, how does this fit with the definitions and statements in 
Kendall (1984)? Is there a publication that extends Kendall (1984) to the use 
of full landmark configurations and explains how they are (mathematically) 
related to the sphere with radius 0.5 (for all numbers and dimensions of 
landmarks)? Related to this question: what do the points on the sphere of 
radius 0.5 in those publications look like? Are they equivalence classes, full 
landmark configurations, or 3 cartesian coordinates representing triangles? Are 
they really scaled to unit centroid size as the shapes on the pre-shape sphere 
[= elements of equivalence classes in shape space]?

The second question is: Why do we need a tangent space projection? I understand 
that the superimposed landmark configurations lie on a hyper-hemisphere and I 
know the argument that standard statistical procedures need a linear space. 
Yet, the superimposed landmark configurations are matrices or vectors, 
depending on how they are formatted, for which we can compute Euclidean 
distances. Where exactly do the statistical tests go wrong if we use the 
superimposed landmark configurations without tangent space projection and 
calculate Euclidean distances?
If I, for example, think about MANOVAs as suggested by Anderson (2001, Austral 
Ecology), I guess that the mean shapes of the groups need to be calculated to 
be able to calculate the different sums of squares. If the mean “shape” is 
calculated by group-wisely simply calculating the mean of each of the 
coordinates, the resulting mean “shape” of each group lies within the 
hyper-hemisphere of radius 1. So the mean “shape” is not a shape because the 
centroid size is not standardized. Yet, if I got all distance calculations 
correctly (see attached R-script 
“Compare_distance_measures_in_original_and_tangent_space.R”), I find that the 
Euclidean distances between the mean “shapes” inside the hyper-hemisphere are 
slightly closer to the corresponding Procrustes distances than the Euclidean 
distances in tangent space; the Procrustes distances have been calculated by 
rescaling the mean “shapes” to unit centroid size followed by determining the 
arc length between them. If the mean “shapes” inside the hyper-hemisphere are 
rescaled to unit centroid size, then the Euclidean distances between them are 
even closer to the Procrustes distances.
In addition, if I simulate groups of landmark configurations, superimpose them 
without and with tangent space projection, and test for significant differences 
between the groups, I feel that the decision on the significance of the group 
differences is correct slightly more often if it is based on the superimposed 
landmark sets without tangent space projection (not exhaustively or formally 
tested; see R-script 
“compare_ProcrustesMANOVA_in_original_and_tangent_space.R”).

And one last, more general question: If all landmark configurations are 
superimposed onto a common mean shape, does this also minimize the Procrustes 
distances (measured as arc length) between all pairs of landmark configurations 
and between the mean shapes of sub-groups of landmark configurations?

Thanks a lot for your insights!

Kind regards
Karo
--
Dr. Karolin Engelkes
Institute of Evolutionary Biology and Animal Ecology
University of Bonn

Phone: +49 (0) 228 73 5481

An der Immenburg 1
53121 Bonn
Germany
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