plotSampDist: Plot(s) of simulated sampling distributions

In jhmaindonald/DAAG: Data Analysis and Graphics Data and Functions

Description

Plots are based on the output from simulateSampDist(). By default, both density plots and normal probability plots are given, for a sample from the specified population and for samples of the relevant size(s)

Usage

plotSampDist(sampvalues, graph = c("density", "qq"), cex = 0.925,
             titletext = "Empirical sampling distributions of the",
             popsample=TRUE, ...)

Arguments

sampvalues	Object output from simulateSampDist()
graph	Either or both of "density" and "qq"
cex	Character size parameter, relative to default
titletext	Title for graph
popsample	If TRUE show distribution of random sample from population
...	Other graphics parameters

Value

Plots graph(s), as described above.

Author(s)

John Maindonald

References

Maindonald, J.H. and Braun, W.J. (3rd edn, 2010) “Data Analysis and Graphics Using R”, Sections 3.3 and 3.4.

See Also

See Also help(simulateSampDist)

Examples

## By default, sample from normal population
simAvs <- simulateSampDist()
par(pty="s")
plotSampDist(simAvs)
## Sample from empirical distribution
simAvs <- simulateSampDist(rpop=rivers)
plotSampDist(simAvs)

## The function is currently defined as
function(sampvalues, graph=c("density", "qq"), cex=0.925,
           titletext="Empirical sampling distributions of the",
           popsample=TRUE, ...){
    if(length(graph)==2)oldpar <- par(mfrow=c(1,2), mar=c(3.1,4.1,1.6,0.6),
               mgp=c(2.5, 0.75, 0), oma=c(0,0,1.5,0), cex=cex)
    values <- sampvalues$values
    numINsamp <- sampvalues$numINsamp
    funtxt <- sampvalues$FUN
    nDists <- length(numINsamp)+1
    nfirst <- 2
    legitems <- paste("Size", numINsamp)
    if(popsample){nfirst <- 1
                  legitems <- c("Size 1", legitems)
                }
    if(match("density", graph)){
      popdens <- density(values[,1], ...)
      avdens <- vector("list", length=nDists)
      maxht <- max(popdens$y)
      ## For each sample size specified in numINsamp, calculate mean
      ## (or other statistic specified by FUN) for numsamp samples
      for(j in nfirst:nDists){
        av <- values[, j]
        avdens[[j]] <- density(av, ...)
        maxht <- max(maxht, avdens[[j]]$y)
      }
    }
    if(length(graph)>0)
      for(graphtype in graph){
        if(graphtype=="density"){
          if(popsample)
          plot(popdens, ylim=c(0, 1.2*maxht), type="l", yaxs="i",
               main="")
          else plot(avdens[[2]], type="n", ylim=c(0, 1.2*maxht),
                    yaxs="i", main="")
          for(j in 2:nDists)lines(avdens[[j]], col=j)
          legend("topleft",
                 legend=legitems,
                 col=nfirst:nDists, lty=rep(1,nDists-nfirst+1), cex=cex)
        }
        if(graphtype=="qq"){
          if(popsample) qqnorm(values[,1], main="")
          else qqnorm(values[,2], type="n")
          for(j in 2:nDists){
            qqav <- qqnorm(values[, j], plot.it=FALSE)
            points(qqav, col=j, pch=j)
           }
            legend("topleft", legend=legitems,
                   col=nfirst:nDists, pch=nfirst:nDists, cex=cex)
       }
      }
    if(par()$oma[3]>0){
      outer <- TRUE
      line=0
    }  else
    {
      outer <- FALSE
      line <- 1.25
    }
    if(!is.null(titletext))
      mtext(side=3, line=line,
            paste(titletext, funtxt),
            cex=1.1, outer=outer)
    if(length(graph)>1)par(oldpar)
  }

jhmaindonald/DAAG documentation built on May 3, 2019, 3:13 p.m.