search for: predint

...fit = TRUE) pred.w.clim <- predict(lm(y ~ x), new, interval = "confidence", se.fit = TRUE) (z.confInt <- with(pred.w.clim, (fit[,3]-fit[,2])/se.fit)) pnorm(-z.confInt/2) s.pred <- sqrt(with(pred.w.plim, se.fit^2+residual.scale^2)) (z.predInt <- with(pred.w.plim, (fit[,3]-fit[,2])/s.pred)) pnorm(-z.predInt/2) ** This gives me 0.01537207. I do not understand why it's not 0.025 with level = 0.95. Can someone help me understand this? Thanks, Spencer Graves

...missing values and NaN's not allowed if 'na.rm' is FALSE" The error appears to come from the function getPredictiveIntervals, specifically the lines: for (i in 1:nrow(predDistr)) { predDistr[i, ] = error(mean = pred[i, ], par = parMatrix[i, ]) } predInt = getCredibleIntervals(sampleMatrix = predDistr, quantiles = quantiles) I suspect lower and upper bounds on the parameters are not being enforced leading to a negative standard deviation being passed to rnorm?. Any suggestions on how to proceed would be welcome. Code: #run the example...

...h correct df, not the standard-normal > distribution: > > > pt(-z.confInt/2, df=13) > ??? 1???? 2???? 3???? 4???? 5???? 6???? 7???? 8???? 9??? 10??? 11 > 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 > ?? 12??? 13 > 0.025 0.025 > > > pt(-z.predInt/2, df=13) > ??? 1???? 2???? 3???? 4???? 5???? 6???? 7???? 8???? 9??? 10??? 11 > 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 0.025 > ?? 12??? 13 > 0.025 0.025 > > I hope this helps, > ?John