inst/doc/Ch_multidimensional_scaling.R

In HSAUR3: A Handbook of Statistical Analyses Using R (3rd Edition)

### R code from vignette source 'Ch_multidimensional_scaling.Rnw'

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### code chunk number 1: setup
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rm(list = ls())
s <- search()[-1]
s <- s[-match(c("package:base", "package:stats", "package:graphics", "package:grDevices",
                "package:utils", "package:datasets", "package:methods", "Autoloads"), s)]
if (length(s) > 0) sapply(s, detach, character.only = TRUE)
if (!file.exists("tables")) dir.create("tables")
if (!file.exists("figures")) dir.create("figures")
set.seed(290875)
options(prompt = "R> ", continue = "+  ",
    width = 63, # digits = 4, 
    show.signif.stars = FALSE,
    SweaveHooks = list(leftpar = function() 
        par(mai = par("mai") * c(1, 1.05, 1, 1)),
        bigleftpar = function()
        par(mai = par("mai") * c(1, 1.7, 1, 1))))
HSAURpkg <- require("HSAUR3")
if (!HSAURpkg) stop("cannot load package ", sQuote("HSAUR3"))
rm(HSAURpkg)
 ### </FIXME> hm, R-2.4.0 --vanilla seems to need this
a <- Sys.setlocale("LC_ALL", "C")
 ### </FIXME>
book <- TRUE
refs <- cbind(c("AItR", "DAGD", "SI", "CI", "ANOVA", "MLR", "GLM", 
                "DE", "RP", "GAM", "SA", "ALDI", "ALDII", "SIMC", "MA", "PCA", 
                "MDS", "CA"), 1:18)
ch <- function(x) {
    ch <- refs[which(refs[,1] == x),]
    if (book) {
        return(paste("Chapter~\\\\ref{", ch[1], "}", sep = ""))
    } else {
        return(paste("Chapter~", ch[2], sep = ""))
    }
}
if (file.exists("deparse.R"))
    source("deparse.R")

setHook(packageEvent("lattice", "attach"), function(...) {
    lattice.options(default.theme = 
        function()
            standard.theme("pdf", color = FALSE))
    })


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### code chunk number 2: singlebook
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book <- FALSE


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### code chunk number 3: MDS-setup
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x <- library("ape")
library("wordcloud")


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### code chunk number 4: MDS-voles-cmdscale
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data("watervoles", package = "HSAUR3")
voles_mds <- cmdscale(watervoles, k = 13, eig = TRUE)
voles_mds$eig


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### code chunk number 5: MDS-voles-criterion1
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sum(abs(voles_mds$eig[1:2]))/sum(abs(voles_mds$eig)) 


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### code chunk number 6: MDS-voles-criterion2
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sum((voles_mds$eig[1:2])^2)/sum((voles_mds$eig)^2)


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### code chunk number 7: MDS-watervoles-plot
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x <- voles_mds$points[,1]
y <- voles_mds$points[,2]
plot(x, y, xlab = "Coordinate 1", ylab = "Coordinate 2",
     xlim = range(x)*1.2, type = "n")
textplot(x, y, words = colnames(watervoles), new = FALSE)


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### code chunk number 8: MDS-watervoles-mst
###################################################
library("ape")
st <- mst(watervoles)
plot(x, y, xlab = "Coordinate 1", ylab = "Coordinate 2",
     xlim = range(x)*1.2, type = "n")
for (i in 1:nrow(watervoles)) {
    w1 <- which(st[i, ] == 1)
    segments(x[i], y[i], x[w1], y[w1])
}
textplot(x, y, words = colnames(watervoles), new = FALSE)


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### code chunk number 9: MDS-voting
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library("MASS")
data("voting", package = "HSAUR3")
voting_mds <- isoMDS(voting)


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### code chunk number 10: MDS-voting-plot
###################################################
x <- voting_mds$points[,1]
y <- voting_mds$points[,2]
plot(x, y, xlab = "Coordinate 1", ylab = "Coordinate 2",
     xlim = range(voting_mds$points[,1])*1.2, type = "n")
textplot(x, y, words = colnames(voting), new = FALSE)
voting_sh <- Shepard(voting[lower.tri(voting)], 
                     voting_mds$points)


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### code chunk number 11: MDS-voting-Shepard
###################################################
plot(voting_sh, pch = ".", xlab = "Dissimilarity", 
     ylab = "Distance", xlim = range(voting_sh$x), 
     ylim = range(voting_sh$x))
lines(voting_sh$x, voting_sh$yf, type = "S")