[Analogue-commits] r363 - pkg/vignettes

[noreply at r-forge.r-project.org]

Author: gsimpson
Date: 2013-10-01 05:17:41 +0200 (Tue, 01 Oct 2013)
New Revision: 363

Modified:
   pkg/vignettes/analogue_methods.Rnw
Log:
name some chunks

Modified: pkg/vignettes/analogue_methods.Rnw
===================================================================
--- pkg/vignettes/analogue_methods.Rnw	2013-10-01 03:06:43 UTC (rev 362)
+++ pkg/vignettes/analogue_methods.Rnw	2013-10-01 03:17:41 UTC (rev 363)
@@ -118,7 +118,7 @@
 \section[Using analogue]{Using \pkg{analogue}}\label{using_analogue}
 This section contains a worked example of how to use the \pkg{analogue} package to fit MAT transfer function models and to perform analogue matching. The \pkg{analogue} package first has to be loaded before it can be used:
 
-<<>>=
+<<loadPackage>>=
 library("analogue")
 @
 
@@ -126,7 +126,7 @@
 
 To illustrate \pkg{analogue}, the Surface Waters Acidification Project (SWAP) diatom:pH training set is used \citep{swapredbook}, along with diatom counts from a sediment core taken from the Round Loch of Glenhead, Galloway, Scotland \citep{604}. The data sets also need to be loaded before they can be used:
 \label{join}
-<<>>=
+<<loadData>>=
 data(swapdiat, swappH, rlgh, package = "analogue")
 @
 
@@ -141,7 +141,7 @@
 
 The data frame of diatom counts (\code{x}), must have the same columns (species) as the data frame of counts for the sediment core for which MAT reconstructions are required. To ensure that both data frames have the same set of columns, the \code{join} function is used to merge the two data sets.
 
-<<>>=
+<<joinData>>=
 dat <- join(swapdiat, rlgh, verbose = TRUE)
 @
 
@@ -151,14 +151,14 @@
 
 By convention, dissimilarity coefficients are defined for proportional data. As the data used in this example are percentages we need to convert them to proportions. We extract each of the merged data sets (the components of \code{dat}) back into the training set and the fossil set, converting the data into proportions as we do so.
 
-<<>>=
+<<convertToPercent>>=
 swapdiat <- dat$swapdiat / 100
 rlgh <- dat$rlgh / 100
 @
 
 The data are now ready for analysis. We will fit a MAT model to the SWAP training set using the squared chord distance (SCD) coefficient:
 
-<<>>=
+<<applyMat>>=
 swap.mat <- mat(swapdiat, swappH, method = "SQchord")
 @