[Vegan-commits] r1918 - in branches/2.0: inst man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sat Oct 1 07:14:23 CEST 2011
Author: jarioksa
Date: 2011-10-01 07:14:21 +0200 (Sat, 01 Oct 2011)
New Revision: 1918
Modified:
branches/2.0/inst/ChangeLog
branches/2.0/man/add1.cca.Rd
branches/2.0/man/deviance.cca.Rd
branches/2.0/man/envfit.Rd
branches/2.0/man/ordistep.Rd
branches/2.0/man/ordisurf.Rd
Log:
merge r1914,1916: doc updates
Modified: branches/2.0/inst/ChangeLog
===================================================================
--- branches/2.0/inst/ChangeLog 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/inst/ChangeLog 2011-10-01 05:14:21 UTC (rev 1918)
@@ -4,6 +4,8 @@
Version 2.0-1 (opened September 8, 2011)
+ * merge r1916: ordisurf.Rd references.
+ * merge r1914: example speed-up.
* r1897, 1840, 1825, 1823: copy clamtest (at r1897),
summary.clamtest, print.summary.clamtest, plot.clamtest (all at
r1823) and clamtest.Rd (at r1897)
Modified: branches/2.0/man/add1.cca.Rd
===================================================================
--- branches/2.0/man/add1.cca.Rd 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/man/add1.cca.Rd 2011-10-01 05:14:21 UTC (rev 1918)
@@ -72,8 +72,10 @@
data(dune.env)
## Automatic model building based on AIC but with permutation tests
step(cca(dune ~ 1, dune.env), reformulate(names(dune.env)), test="perm")
-## The same, but based on permutation P-values
+## see ?ordistep to do the same, but based on permutation P-values
+\dontrun{
ordistep(cca(dune ~ 1, dune.env), reformulate(names(dune.env)), perm.max=200)
+}
## Manual model building
## -- define the maximal model for scope
mbig <- rda(dune ~ ., dune.env)
Modified: branches/2.0/man/deviance.cca.Rd
===================================================================
--- branches/2.0/man/deviance.cca.Rd 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/man/deviance.cca.Rd 2011-10-01 05:14:21 UTC (rev 1918)
@@ -91,15 +91,9 @@
data(dune.env)
chisq.test(dune)
deviance(cca(dune))
-# Backward elimination from a complete model "dune ~ ."
-ord <- cca(dune ~ ., dune.env)
-ord
-step(ord)
# Stepwise selection (forward from an empty model "dune ~ 1")
+ord <- cca(dune ~ ., dune.env)
step(cca(dune ~ 1, dune.env), scope = formula(ord))
-# ANOVA: added variable + the first left out
-anova(cca(dune ~ Moisture + Management, dune.env), permut=200,
- by = "terms")
}
\keyword{ multivariate }
\keyword{ models }
Modified: branches/2.0/man/envfit.Rd
===================================================================
--- branches/2.0/man/envfit.Rd 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/man/envfit.Rd 2011-10-01 05:14:21 UTC (rev 1918)
@@ -187,7 +187,7 @@
data(dune.env)
attach(dune.env)
ord <- cca(dune)
-fit <- envfit(ord ~ Moisture + A1, dune.env)
+fit <- envfit(ord ~ Moisture + A1, dune.env, perm = 0)
plot(ord, type = "n")
ordispider(ord, Moisture, col="skyblue")
points(ord, display = "sites", col = as.numeric(Moisture), pch=16)
Modified: branches/2.0/man/ordistep.Rd
===================================================================
--- branches/2.0/man/ordistep.Rd 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/man/ordistep.Rd 2011-10-01 05:14:21 UTC (rev 1918)
@@ -144,8 +144,9 @@
ordistep(mod1, perm.max = 200)
## Example of ordistep, forward
+\dontrun{
ordistep(mod0, scope = formula(mod1), direction="forward", perm.max = 200)
-
+}
### Mite data
data(mite)
data(mite.env)
@@ -159,9 +160,11 @@
step.res$anova # Summary table
## Example of ordiR2step with direction = "forward"
+\dontrun{
step.res <- ordiR2step(mod0, scope = formula(mod1), direction="forward")
step.res$anova # Summary table
}
+}
\keyword{ multivariate }
\keyword{ models }
Modified: branches/2.0/man/ordisurf.Rd
===================================================================
--- branches/2.0/man/ordisurf.Rd 2011-09-30 16:39:18 UTC (rev 1917)
+++ branches/2.0/man/ordisurf.Rd 2011-10-01 05:14:21 UTC (rev 1918)
@@ -102,17 +102,19 @@
to the graphical functions. See Note below for exceptions.}
}
-\details{
- Function \code{ordisurf} fits a smooth surface using thinplate splines
- in \code{\link[mgcv]{gam}}, and uses \code{\link[mgcv]{predict.gam}}
- to find fitted values in a regular grid. The smooth surface can be
- fitted with an extra penalty that allows the entire smoother to be
- penalized back to 0 degrees of freedom, effectively removing the term
- from the model. The addition of this extra penalty is invoked by
- setting argument \code{select} to \code{TRUE}. The function plots the
- fitted contours with convex hull of data points either over an
+\details{
+
+ Function \code{ordisurf} fits a smooth surface using thinplate
+ splines (Wood 2003) in \code{\link[mgcv]{gam}}, and uses
+ \code{\link[mgcv]{predict.gam}} to find fitted values in a regular
+ grid. The smooth surface can be fitted with an extra penalty that
+ allows the entire smoother to be penalized back to 0 degrees of
+ freedom, effectively removing the term from the model (see Marra &
+ Wood, 2011). The addition of this extra penalty is invoked by
+ setting argument \code{select} to \code{TRUE}. The function plots
+ the fitted contours with convex hull of data points either over an
existing ordination diagram or draws a new plot. If \code{select ==
- TRUE} and the smooth is effectively penalised out of the model, no
+ TRUE} and the smooth is effectively penalised out of the model, no
contours will be plotted.
\code{\link[mgcv]{gam}} determines the degree of smoothness for the
@@ -175,6 +177,17 @@
illustration of this.
}
+\references{
+
+ Marra, G.P & Wood, S.N. (2011) Practical variable selection for
+ generalized additive models. \emph{Comput. Stat. Data Analysis} 55,
+ 2372--2387.
+
+ Wood, S.N. (2003) Thin plate regression splines.
+ \emph{J. R. Statist. Soc. B} 65, 95--114.
+
+}
+
\seealso{ For basic routines \code{\link[mgcv]{gam}},
and \code{\link{scores}}. Function
\code{\link{envfit}} provides a more traditional and compact
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