Message-ID: <20121109085016.65735uwoe30zdfs4@www.staffmail.ed.ac.uk>
Date: 2012-11-09T08:50:16Z
From: Jarrod Hadfield
Subject: predict with newdata -- New version of MCMCglmm
In-Reply-To: <509C4BDC.3050306@u.washington.edu>
Hi Dave,
I did intend to make it part of the current version. The difficulty is
that if the fixed predictors in newdata have less levels than those in
data, then things like the intercept will have a different
interpretation. If data and newdata could be guaranteed to have the
same levels for fixed terms (and terms within a variance.function)
then it would be more straightforward. I guess I could return an error
if this was not the case, and allow predictions on newdata when these
conditions were satisfied....
Cheers,
Jarrod
Quoting David Atkins <datkins at u.washington.edu> on Thu, 08 Nov 2012
16:18:36 -0800:
>
> [Posting to list as others might be interested...]
>
> Jarrod--
>
> Very cool to see the continued development of MCMCglmm.
>
> My typical use of predict() functions (across various R
> regression-based commands) involves generating predictions on
> newdata -- typically to help interpret models involving non-linear
> terms and/or interactions. As far as I can tell, the predict
> function in v2.17 of MCMCglmm does not yet incorporate new data.
>
> Any guess on when the newdata argument in predict.MCMCglmm might
> "come online"?
>
> cheers, Dave
>
> --
> Dave Atkins, PhD
>
> Department of Psychiatry and Behavioral Science
> University of Washington
> datkins at u.washington.edu
> 206-616-3879
> http://depts.washington.edu/cshrb/
>
> "We are drowning in information and starving for knowledge."
> Rutherford Roger
>
> _______________________________________________
> R-sig-mixed-models at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
--
The University of Edinburgh is a charitable body, registered in
Scotland, with registration number SC005336.