stanLogTransformedPlot.R

meanPred <- apply(Sims, 2, mean)
LwPred <- apply(Sims, 2, quantile, 0.05)
UpPred <- apply(Sims, 2, quantile, 0.95)
xlim <- c(min(icecream$temp)*0.95, max(temp)*1.05)
ylim <- c(floor(min(units)*0.95),
          ceiling(max(units)*1.05))
plotStan <- lapply(
  seq(along=temp),
  function(i){
    stp = 251
    d = density(Sims[, i, ], n=stp)
    y = seq(ylim[1], ylim[2], length=stp)
    z = approx(d$x, d$y, y)$y 
    z[is.na(z)] <- 0
    x = rep(icecream$temp[i], stp)
    z0 = rep(0, stp)
    return(list(x=x, y=y, z0=z0, z=z))
  }
)
# https://gist.github.com/mages/dedfb0d97082f0f0e0ab
glmModelPlot(x=temp, y=units,
             xlim=xlim, ylim=ylim,
             meanPred = meanPred, LwPred = LwPred,
             UpPred = UpPred, plotData = plotStan,
             main = "Log-transformed LM prediction")