[adegenet-commits] r552 - pkg/man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Mon Feb 8 13:19:20 CET 2010


Author: jombart
Date: 2010-02-08 13:19:19 +0100 (Mon, 08 Feb 2010)
New Revision: 552

Added:
   pkg/man/find.clusters.Rd
Removed:
   pkg/man/find.clusters.R
Log:
renamde file


Deleted: pkg/man/find.clusters.R
===================================================================
--- pkg/man/find.clusters.R	2010-02-08 12:11:06 UTC (rev 551)
+++ pkg/man/find.clusters.R	2010-02-08 12:19:19 UTC (rev 552)
@@ -1,122 +0,0 @@
-\encoding{UTF-8}
-\name{find.clusters}
-\alias{find.clusters}
-\alias{find.clusters.data.frame}
-\alias{find.clusters.matrix}
-\alias{find.clusters.genind}
-\title{}
-\description{ == IN PROGRESS ==
-  These functions implement the Discriminant Analysis of Principal Components
-  (FIND.CLUSTERS). See 'details' section for a succint description of the method. FIND.CLUSTERS
-  implementation calls upon \code{dudi.pca} from the \code{ade4} package and
-  \code{lda} from the \code{MASS} package.
-
- \code{find.clusters} performs the FIND.CLUSTERS on a \code{data.frame}, a \code{matrix}, or a
- \code{\linkS4class{genind}} object, and returns an object with class
- \code{find.clusters}. If data are stored in a \code{data.frame} or a \code{matrix},
- these have to be quantitative data (i.e., \code{numeric} or \code{integers}),
- as opposed to \code{characters} or \code{factors}.
-
-}
-\usage{
-\method{find.clusters}{data.frame}()
-
-\method{find.clusters}{matrix}()
-
-\method{find.clusters}{genind}()
-
-}
-\arguments{
-\item{x}{\code{a data.frame}, \code{matrix}, or \code{\linkS4class{genind}}
-  object. For the \code{data.frame} and \code{matrix} arguments, only
-  quantitative variables should be provided.}
-\item{grp,pop}{a \code{factor} indicating the group membership of individuals}
-\item{n.pca}{an \code{integer} indicating the number of axes retained in the
-  Principal Component Analysis (PCA) step. If \code{NULL}, interactive selection is triggered.}
-\item{n.da}{an \code{integer} indicating the number of axes retained in the
-  Discriminant Analysis step. If \code{NULL}, interactive selection is triggered.}
-\item{center}{a \code{logical} indicating whether variables should be centred to
-mean 0 (TRUE, default) or not (FALSE). Always TRUE for \linkS4class{genind} objects.}
-\item{scale}{a \code{logical} indicating whether variables should be scaled
-  (TRUE) or not (FALSE, default). Scaling consists in dividing variables by their
-  (estimated) standard deviation to account for trivial differences in
-  variances. Further scaling options are available for \linkS4class{genind}
-  objects (see argument \code{scale.method}).}
-\item{var.contrib,all.contrib}{a \code{logical} indicating whether the
-  contribution of original variables (alleles, for \linkS4class{genind} objects)
-  should be provided (TRUE) or not (FALSE, default). Such output can be useful,
-  but can also create huge matrices when there the original size of the dataset
-  is huge.}
-\item{pca.select}{a \code{character} indicating the mode of selection of PCA
-  axes, matching approximately "nbEig" or "percVar". For "nbEig", the user
-  has to specify the number of axes retained (interactively, or via
-  \code{n.pca}). For "percVar", the user has to specify the minimum amount of
-  the total variance to be preserved by the retained axes, expressed as a
-  percentage (interactively, or via \code{perc.pca}).  }
-\item{perc.pca}{a \code{numeric} value between 0 and 100 indicating the
-  minimal percentage of the total variance of the data to be expressed by the
-  retained axes of PCA.}
-\item{\ldots}{further arguments to be passed to other functions. For
-  \code{find.clusters.matrix}, arguments are to match those of \code{find.clusters.data.frame}.}
-\item{scale.method}{a \code{character} specifying the scaling method to be used
-  for allele frequencies, which must match "sigma" (usual estimate of standard
-  deviation) or "binom" (based on binomial distribution). See \code{\link{scaleGen}} for
-  further details.}
-\item{truenames}{a \code{logical} indicating whether true (i.e., user-specified)
-  labels should be used in object outputs (TRUE, default) or not (FALSE).}
-\item{xax,yax}{\code{integers} specifying which principal components of FIND.CLUSTERS
-  should be shown in x and y axes. }
-\item{col}{a suitable color to be used for groups. Not that the specified vector
-should match the number of groups, not the number of individuals.}
-\item{posi,bg,ratio,csub}{arguments used to customize the inset in scatterplots
-  of FIND.CLUSTERS results. See \code{\link[pkg:ade4]{add.scatter}} documentation in the
-  ade4 package for
-  more details.}
-\item{only.grp}{a \code{character} vector indicating which groups should be
-  displayed. Values should match values of \code{x$grp}. If \code{NULL}, all
-  results are displayed}
-\item{subset}{\code{integer} or \code{logical} vector indicating which
-  individuals should be displayed. If \code{NULL}, all
-  results are displayed}
-\item{cex.lab}{a \code{numeric} indicating the size of labels.}
-\item{pch}{a \code{numeric} indicating the type of point to be used to indicate
-  the prior group of individuals (see \code{\link{points}} documentation for
-  more details).}
-}
-\details{
-
-}
-\value{
-  The class \code{find.clusters} is a list with the following
-  components:\cr
-  \item{}{}
-
-}
-\references{
-Jombart, T., Devillard, S. and Balloux, F.
-Discriminant analysis of principal components: a new method for the analysis of
-genetically structured populations. Submitted to \emph{PLoS genetics}.
-}
-\seealso{
-    \code{\link{}}
-    \code{\link{}}
-    \code{\link{}}
-    \code{\link{}}
-    \code{\link{}}
-}
-\author{ Thibaut Jombart \email{t.jombart at imperial.ac.uk} }
-\examples{
-## data(find.clustersIllus), data(eHGDP), and data(H3N2) illustrate the find.clusters
-## see ?find.clustersIllus, ?eHGDP, ?H3N2
-##
-
-example(find.clusters)
-
-
-\dontrun{
-example(eHGDP)
-example(H3N2)
-}
-
-}
-\keyword{multivariate}

Copied: pkg/man/find.clusters.Rd (from rev 551, pkg/man/find.clusters.R)
===================================================================
--- pkg/man/find.clusters.Rd	                        (rev 0)
+++ pkg/man/find.clusters.Rd	2010-02-08 12:19:19 UTC (rev 552)
@@ -0,0 +1,122 @@
+\encoding{UTF-8}
+\name{find.clusters}
+\alias{find.clusters}
+\alias{find.clusters.data.frame}
+\alias{find.clusters.matrix}
+\alias{find.clusters.genind}
+\title{}
+\description{ == IN PROGRESS ==
+  These functions implement the Discriminant Analysis of Principal Components
+  (FIND.CLUSTERS). See 'details' section for a succint description of the method. FIND.CLUSTERS
+  implementation calls upon \code{dudi.pca} from the \code{ade4} package and
+  \code{lda} from the \code{MASS} package.
+
+ \code{find.clusters} performs the FIND.CLUSTERS on a \code{data.frame}, a \code{matrix}, or a
+ \code{\linkS4class{genind}} object, and returns an object with class
+ \code{find.clusters}. If data are stored in a \code{data.frame} or a \code{matrix},
+ these have to be quantitative data (i.e., \code{numeric} or \code{integers}),
+ as opposed to \code{characters} or \code{factors}.
+
+}
+\usage{
+\method{find.clusters}{data.frame}()
+
+\method{find.clusters}{matrix}()
+
+\method{find.clusters}{genind}()
+
+}
+\arguments{
+\item{x}{\code{a data.frame}, \code{matrix}, or \code{\linkS4class{genind}}
+  object. For the \code{data.frame} and \code{matrix} arguments, only
+  quantitative variables should be provided.}
+\item{grp,pop}{a \code{factor} indicating the group membership of individuals}
+\item{n.pca}{an \code{integer} indicating the number of axes retained in the
+  Principal Component Analysis (PCA) step. If \code{NULL}, interactive selection is triggered.}
+\item{n.da}{an \code{integer} indicating the number of axes retained in the
+  Discriminant Analysis step. If \code{NULL}, interactive selection is triggered.}
+\item{center}{a \code{logical} indicating whether variables should be centred to
+mean 0 (TRUE, default) or not (FALSE). Always TRUE for \linkS4class{genind} objects.}
+\item{scale}{a \code{logical} indicating whether variables should be scaled
+  (TRUE) or not (FALSE, default). Scaling consists in dividing variables by their
+  (estimated) standard deviation to account for trivial differences in
+  variances. Further scaling options are available for \linkS4class{genind}
+  objects (see argument \code{scale.method}).}
+\item{var.contrib,all.contrib}{a \code{logical} indicating whether the
+  contribution of original variables (alleles, for \linkS4class{genind} objects)
+  should be provided (TRUE) or not (FALSE, default). Such output can be useful,
+  but can also create huge matrices when there the original size of the dataset
+  is huge.}
+\item{pca.select}{a \code{character} indicating the mode of selection of PCA
+  axes, matching approximately "nbEig" or "percVar". For "nbEig", the user
+  has to specify the number of axes retained (interactively, or via
+  \code{n.pca}). For "percVar", the user has to specify the minimum amount of
+  the total variance to be preserved by the retained axes, expressed as a
+  percentage (interactively, or via \code{perc.pca}).  }
+\item{perc.pca}{a \code{numeric} value between 0 and 100 indicating the
+  minimal percentage of the total variance of the data to be expressed by the
+  retained axes of PCA.}
+\item{\ldots}{further arguments to be passed to other functions. For
+  \code{find.clusters.matrix}, arguments are to match those of \code{find.clusters.data.frame}.}
+\item{scale.method}{a \code{character} specifying the scaling method to be used
+  for allele frequencies, which must match "sigma" (usual estimate of standard
+  deviation) or "binom" (based on binomial distribution). See \code{\link{scaleGen}} for
+  further details.}
+\item{truenames}{a \code{logical} indicating whether true (i.e., user-specified)
+  labels should be used in object outputs (TRUE, default) or not (FALSE).}
+\item{xax,yax}{\code{integers} specifying which principal components of FIND.CLUSTERS
+  should be shown in x and y axes. }
+\item{col}{a suitable color to be used for groups. Not that the specified vector
+should match the number of groups, not the number of individuals.}
+\item{posi,bg,ratio,csub}{arguments used to customize the inset in scatterplots
+  of FIND.CLUSTERS results. See \code{\link[pkg:ade4]{add.scatter}} documentation in the
+  ade4 package for
+  more details.}
+\item{only.grp}{a \code{character} vector indicating which groups should be
+  displayed. Values should match values of \code{x$grp}. If \code{NULL}, all
+  results are displayed}
+\item{subset}{\code{integer} or \code{logical} vector indicating which
+  individuals should be displayed. If \code{NULL}, all
+  results are displayed}
+\item{cex.lab}{a \code{numeric} indicating the size of labels.}
+\item{pch}{a \code{numeric} indicating the type of point to be used to indicate
+  the prior group of individuals (see \code{\link{points}} documentation for
+  more details).}
+}
+\details{
+
+}
+\value{
+  The class \code{find.clusters} is a list with the following
+  components:\cr
+  \item{}{}
+
+}
+\references{
+Jombart, T., Devillard, S. and Balloux, F.
+Discriminant analysis of principal components: a new method for the analysis of
+genetically structured populations. Submitted to \emph{PLoS genetics}.
+}
+\seealso{
+    \code{\link{}}
+    \code{\link{}}
+    \code{\link{}}
+    \code{\link{}}
+    \code{\link{}}
+}
+\author{ Thibaut Jombart \email{t.jombart at imperial.ac.uk} }
+\examples{
+## data(find.clustersIllus), data(eHGDP), and data(H3N2) illustrate the find.clusters
+## see ?find.clustersIllus, ?eHGDP, ?H3N2
+##
+
+example(find.clusters)
+
+
+\dontrun{
+example(eHGDP)
+example(H3N2)
+}
+
+}
+\keyword{multivariate}



More information about the adegenet-commits mailing list