https://github.com/cran/shapes
Tip revision: ac9bd97a2bfdf99a56dffd73575735ea6a2b15da authored by Ian Dryden on 10 December 2007, 00:00:00 UTC
version 1.1-1
version 1.1-1
Tip revision: ac9bd97
testmeanshapes.Rd
\name{testmeanshapes}
\alias{testmeanshapes}
%- Also NEED an `\alias' for EACH other topic documented here.
\title{Tests for mean shape difference}
\description{
Carries out Hotelling's $T^2$ or Goodall's $F$ test to examine differences in mean shape
between two independent populations, for $m>=2$ dimensional data.
The procedure uses complex eigenanalysis for $m=2$ and iterative
Generalised Procrustes Analysis for $m>2$ dimensions.
}
\usage{
testmeanshapes(A, B, Hotelling = TRUE, tol1 = 1e-05, tol2 = 1e-05)
}
%- maybe also `usage' for other objects documented here.
\arguments{
\item{A}{The random sample for group 1: k x m x n1 array of data, where
k is the number of landmarks, m is dimension and n1 is the sample size}
\item{B}{The random sample for group 2: k x m x n2 array of data, where
k is the number of landmarks, m is dimension and n2 is the sample size}
\item{Hotelling}{Logical. If TRUE then carry out Hotelling's $T^2$ test,
if FALSE carry out Goodall's $F$ test}
\item{tol1}{Tolerance for optimal rotation for the iterative
algorithm ($m>2$): tolerance on the mean sum of squares between successive iterations
(depends on scale of objects)}
\item{tol2}{tolerance for rescale/rotation step for the iterative
algorithm ($m>2$): tolerance on the Riemannian shape distance
between successive mean shapes}
}
\value{
A list with components
\item{F}{the F statistic}
\item{df1 and df2}{degrees of freedom of the F statistic}
\item{pval}{p-value for the test}
\item{Tsq}{the $T^2$ statistic (if Hotelling)}
\item{T.df1 and T.df2}{degrees of freedom of the $T^2$ statistic (if Hotelling)}
\item{Tsq.partition}{the $T^2$ statistic partitioned into
contributions from each of the pooled principal components (if Hotelling)}
\item{F.partition}{the F statistic partitioned into
contributions from each of the pooled principal components (if Hotelling)}
}
\references{Dryden, I.L. and Mardia, K.V. (1998) Statistical Shape Analysis,
Wiley, Chichester. Chapter 7.
Dryden and Mardia (1993) Multivariate shape analysis. Sankhya A, 55:460-480.
Goodall, C. R. (1991). Procrustes methods in the statistical analysis
of shape (with discussion). Journal of the Royal Statistical Society,
Series B, 53: 285-339.
}
\author{Ian Dryden}
\seealso{procGPA}
\examples{
#2D example : female and male Gorillas (cf. Dryden and Mardia, 1998)
data(gorf.dat)
data(gorm.dat)
#Hotelling's Tsq test
test1<-testmeanshapes(gorf.dat,gorm.dat)
#Goodall's isotropic test
test2<-testmeanshapes(gorf.dat,gorm.dat,Hotelling=FALSE)
}
\keyword{multivariate}% at least one, from doc/KEYWORDS