# Plot Bayes or confidence interval density contours over a grid of points (usually dose or time) Density plot for distributions conditional on a variable. A grid of values are specified for the conditioning variable, which is plotted on the horizontal axis. The conditioning variable is typically dose or time ```r DRDensityPlot(x,qL,qH,qlevL=c(0.025,0.05,0.10,0.25), xlim,ylim,xlab='x',ylab='y') ``` ## Arguments - `x`: A grid of conditioning values to be plotted on the horizontal axis. This grid typically represents dose or time. - `qL`: Lower percentiles, confidence or probabiity levels. `qL` is a matrix with rows corresponding to `x`, and columns corresponding to `qlevL`. The percentiles must be increasing in order and less that 0.50. - `qH`: Upper percentiles, confidence or probabiity levels. `qH` levels correspond to the `qL` levels but are ordered from highest to lowest (1-`qlevL`), with the smallest greater than 0.50. - `qlevL`: Density intervals are formed with percentile boundaries at (qlevL,1-qlevL). `qlevL` must be increasing between (0,0.5). - `xlim`: Plot limits for the x-axis - `ylim`: Plot limits for the y-axis - `xlab`: x-axis label - `ylab`: y-axis label ## Details The function takes as input percentiles defining confidence intervals or Bayesian probability intervals at different levels (e.g. 5,95, 25,75) for distributions conditional on a variable that is typically dose or time. Regions defined by different confidence/probability levels are represented by different levels of shading. The input parameter, `qlevL`, is used only to define the input in the matrices `qL` and `qH`. The `qlevL` is not used for any numerical calculations, which must be done before executing the function. ## Returns Plotted output only. ## Author(s) Neal Thomas ## See Also `plotBdensity` ## Examples ```r ## Not run: data('metaData') exdat<-metaData[metaData$taid==32,] msSat<-sum((exdat$sampsize-1)*(exdat$sd)^2)/(sum(exdat$sampsize)-length(exdat$sampsize)) fitout<-fitEmax(exdat$rslt,exdat$dose,modType=3,count=exdat$sampsize, msSat=msSat) dgrid<-seq(0,100,length=100) seout95<-predict(fitout,dgrid,clev=0.95) seout90<-predict(fitout,dgrid,clev=0.9) seout80<-predict(fitout,dgrid,clev=0.8) seout50<-predict(fitout,dgrid,clev=0.5) qlev<-c(0.025,0.05,0.10,0.25) qL<-cbind(seout95$ubdif,seout90$ubdif,seout80$ubdif,seout50$ubdif) qH<-cbind(seout95$lbdif,seout90$lbdif,seout80$lbdif,seout50$lbdif) DRDensityPlot(dgrid,qL,qH,qlevL=qlev,xlab='Dose',ylab='Diff with PBO') ## End(Not run) ```

DRDensityPlot function