Burns, Jonathan (NONUS)
2015-Feb-11 19:03 UTC
[R] prediction intervals for robust regression
I have created robust regression models using least trimmed squares and MM-regression (using the R package robustbase). I am now looking to create prediction intervals for the predicted results. While I have seen some discussion in the literature about confidence intervals on the estimates for robust regression, I haven't had much success in finding out how to create prediction intervals for the results. I was wondering if anyone would be able to provide some direction on how to create these prediction intervals in the robust regression setting. Thanks, Jonathan Burns Sr. Statistician General Dynamics Information Technology Medicare & Medicaid Solutions One West Pennsylvania Avenue Baltimore, MD 21204 (410)-842-1594 Jonathan.Burns1 at gdit.com<mailto:Jonathan.Burns1 at gdit.com> www.gdit.com<http://www.gdit.com/> [[alternative HTML version deleted]]
Presumably you've checked out: http://cran.r-project.org/web/views/Robust.html If you can estimate the variance of parameter estimates, betahat, then you can estimate the variance of a predicted value, X betahat; add the estimated variance of individuals to this if that's what you're looking for (and it's not already available). Further questions should go to a statistics site like stats.stackexchange.com, as statistical questions are off topic here. Cheers, Bert Bert Gunter Genentech Nonclinical Biostatistics (650) 467-7374 "Data is not information. Information is not knowledge. And knowledge is certainly not wisdom." Clifford Stoll On Wed, Feb 11, 2015 at 11:03 AM, Burns, Jonathan (NONUS) <Jonathan.Burns1 at gdit.com> wrote:> I have created robust regression models using least trimmed squares and MM-regression (using the R package robustbase). > > I am now looking to create prediction intervals for the predicted results. While I have seen some discussion in the literature about confidence intervals on the estimates for robust regression, I haven't had much success in finding out how to create prediction intervals for the results. I was wondering if anyone would be able to provide some direction on how to create these prediction intervals in the robust regression setting. > > Thanks, > > Jonathan Burns > Sr. Statistician > General Dynamics Information Technology > Medicare & Medicaid Solutions > One West Pennsylvania Avenue > Baltimore, MD 21204 > (410)-842-1594 > Jonathan.Burns1 at gdit.com<mailto:Jonathan.Burns1 at gdit.com> > www.gdit.com<http://www.gdit.com/> > > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see > 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.
On 11/02/2015 19:38, Bert Gunter wrote:> Presumably you've checked out: > > http://cran.r-project.org/web/views/Robust.html > > If you can estimate the variance of parameter estimates, betahat, then > you can estimate the variance of a predicted value, X betahat; add the > estimated variance of individuals to this if that's what you're > looking for (and it's not already available).But that's not too much use without some idea of the error distribution, and using robust statistics assumes it is non-normal, long-tailed. And it is unusual to have enough data to estimate the tail behaviour of such a distribution. It might be better to do this with a parametric model with a long-tailed error distribution, especially if there is evidence (e.g. from other samples) about the latter.> Further questions should go to a statistics site like > stats.stackexchange.com, as statistical questions are off topic here.Agreed.> > Cheers, > Bert > > Bert Gunter > Genentech Nonclinical Biostatistics > (650) 467-7374 > > "Data is not information. Information is not knowledge. And knowledge > is certainly not wisdom." > Clifford Stoll > > > > > On Wed, Feb 11, 2015 at 11:03 AM, Burns, Jonathan (NONUS) > <Jonathan.Burns1 at gdit.com> wrote: >> I have created robust regression models using least trimmed squares and MM-regression (using the R package robustbase). >> >> I am now looking to create prediction intervals for the predicted results. While I have seen some discussion in the literature about confidence intervals on the estimates for robust regression, I haven't had much success in finding out how to create prediction intervals for the results. I was wondering if anyone would be able to provide some direction on how to create these prediction intervals in the robust regression setting. >> >> Thanks, >> >> Jonathan Burns >> Sr. Statistician >> General Dynamics Information Technology >> Medicare & Medicaid Solutions >> One West Pennsylvania Avenue >> Baltimore, MD 21204 >> (410)-842-1594 >> Jonathan.Burns1 at gdit.com<mailto:Jonathan.Burns1 at gdit.com> >> www.gdit.com<http://www.gdit.com/>-- Brian D. Ripley, ripley at stats.ox.ac.uk Emeritus Professor of Applied Statistics, University of Oxford 1 South Parks Road, Oxford OX1 3TG, UK