Dear Achim, Thanks for the script. It works fine except it sometimes yields extreme wide confidence intervals. That is for a factor level with only a few replications or a level with all zeros. I noticed that the se for those predictions was Nan. Therefore I've added two lines (marked with #% at the end) that set the lower and upper bound to NA when is.na(se). No confidence intervals make, in my opinion, in those cases more sense than c.i. like [1e-200, 1e200].
Best regards, Thierry ------------------------------------------------------------------------ ---- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 thierry.onkel...@inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: Achim Zeileis [mailto:achim.zeil...@wu-wien.ac.at] Verzonden: dinsdag 16 december 2008 16:45 Aan: ONKELINX, Thierry CC: r-help@r-project.org Onderwerp: Re: [R] Prediction intervals for zero inflated Poisson regression Thierry, Simon had written some code for this but we never got round to fully integrate it into the "pscl" package. A file pb.R is attached, but as a disclaimer: I haven't looked at this code for a while. It still seems to work (an example is included at the end) but please check. hth, Z On Tue, 16 Dec 2008, ONKELINX, Thierry wrote: > Dear all, > > I'm using zeroinfl() from the pscl-package for zero inflated Poisson > regression. I would like to calculate (aproximate) prediction intervals > for the fitted values. The package itself does not provide them. Can > this be calculated analyticaly? Or do I have to use bootstrap? > > What I tried until now is to use bootstrap to estimate these intervals. > Any comments on the code are welcome. The data and the model are based > on the examples in zeroinfl(). > > #aproximate prediction intervals with Poisson regression > fm_pois <- glm(art ~ fem, data = bioChemists, family = poisson) > newdata <- na.omit(unique(bioChemists[, "fem", drop = FALSE])) > prediction <- predict(fm_pois, newdata = newdata, se.fit = TRUE) > ci <- data.frame(exp(prediction$fit + matrix(prediction$se.fit, ncol = > 1) %*% c(-1.96, 1.96))) > newdata$fit <- exp(prediction$fit) > newdata <- cbind(newdata, ci) > newdata$model <- "Poisson" > > library(pscl) > #aproximate prediction intervals with zero inflated poisson regression > fm_zip <- zeroinfl(art ~ fem | 1, data = bioChemists) > fit <- predict(fm_zip) > Pearson <- resid(fm_zip, type = "pearson") > VarComp <- resid(fm_zip, type = "response") / Pearson > fem <- bioChemists$fem > bootstrap <- replicate(999, { > yStar <- pmax(round(fit + sample(Pearson) * VarComp, 0), 0) > predict(zeroinfl(yStar ~ fem | 1), newdata = newdata) > }) > newdata0 <- newdata > newdata0$fit <- predict(fm_zip, newdata = newdata, type = "response") > newdata0[, 3:4] <- t(apply(bootstrap, 1, quantile, c(0.025, 0.975))) > newdata0$model <- "Zero inflated" > > #compare the intervals in a nice plot. > newdata <- rbind(newdata, newdata0) > library(ggplot2) > ggplot(newdata, aes(x = fem, y = fit, min = X1, max = X2, colour = > model)) + geom_point(position = position_dodge(width = 0.4)) + > geom_errorbar(position = position_dodge(width = 0.4)) > > > Best regards, > > Thierry > > ------------------------------------------------------------------------ > ---- > ir. Thierry Onkelinx > Instituut voor natuur- en bosonderzoek / Research Institute for Nature > and Forest > Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, > methodology and quality assurance > Gaverstraat 4 > 9500 Geraardsbergen > Belgium > tel. + 32 54/436 185 > thierry.onkel...@inbo.be > www.inbo.be > > To call in the statistician after the experiment is done may be no more > than asking him to perform a post-mortem examination: he may be able to > say what the experiment died of. > ~ Sir Ronald Aylmer Fisher > > The plural of anecdote is not data. > ~ Roger Brinner > > The combination of some data and an aching desire for an answer does not > ensure that a reasonable answer can be extracted from a given body of > data. > ~ John Tukey > > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer > en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is > door een geldig ondertekend document. The views expressed in this message > and any annex are purely those of the writer and may not be regarded as stating > an official position of INBO, as long as the message is not confirmed by a duly > signed document. > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > > Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.
______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
