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shapes

This is the development version of the R package shapes (which will eventually be version 1.2.7). The current released version 1.2.6 is on CRAN at https://cran.r-project.org/web/packages/shapes/index.html

To use this library in R:

   library("devtools")   
   install_github("iandryden/shapes")   
   library(shapes)

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Version

Install

install.packages('shapes')

Monthly Downloads

1,511

Version

1.2.7

License

GPL-2

Maintainer

Ian Dryden

Last Published

February 3rd, 2023

Functions in shapes (1.2.7)

Electrophoresis gel data

Male and Female macaque data

Male macaque data

T2 mouse vertabrae data

Mean shape estimators

Combine two or more groups of configurations

Female macaque data

Human movement data

Female gorilla data

Male chimpanzee data

Male gorilla data

Female orang utan data

Female chimpanzee data

Modes of variation plots for PCA and PNSS

Male orang utan data

Generalised Procrustes analysis

Principal Nested Shape Space Analysis

Plot configurations

Principal Nested Shape Spaces from PCA

Principal Nested Spheres

Procrustes distance

Small T2 mouse vertabrae data

Large T2 mouse vertabrae data

Weighted Procrustes analysis

Control T2 mouse vertabrae data

Ordinary Procrustes analysis

Riemannian shape distance

Riemannian size-and-shape distance

Sooty mangabey data

Canonical variate analysis for shapes

shapes-internal

Internal function(s)

Rigid body transformations

Tests for mean shape difference, including permutation and bootstrap tests

Bookstein's schizophrenia data

Microfossil shell data

Rat skulls data

Sand particle outline data

schizophrenia.dat

Bookstein's schizophrenia data

Tests for mean shape difference using complex arithmetic, including bootstrap and permutation tests.

Principal components analysis for shape

transformations

Calculate similarity transformations

Thin-plate spline transformation grids

Brain landmark data

Bookstein's baseline registration for 2D data

Weighted Frechet mean of covariance matrices

Compute a distance between two covariance matrices

Cortical surface data

Backfit from scores to configuration