[R-sig-ME] FW: Variogram / confint prediction in LMM / time prediction some questions from Switerland area
mudryjm @end|ng |rom b|uew|n@ch
Sun Aug 8 11:17:58 CEST 2021
Sent: Sunday, August 1, 2021 5:32 PM
To: mudryjm <mudryjm using bluewin.ch>
Subject: Re: Variogram / confint prediction in LMM / time prediction some questions from Switerland area
I regret that I am not able to answer your questions at this time. It has been a couple of decades since I worked on the nlme package and I have not kept up with the literature.
I suggest that you send your questions to the R-SIG-Mixed-Models using R-project.org <mailto:R-SIG-Mixed-Models using R-project.org> mailing list. Some information about the list is available at https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
On Sun, Aug 1, 2021 at 9:25 AM mudryjm <mudryjm using bluewin.ch <mailto:mudryjm using bluewin.ch> > wrote:
Dear Mr Bates and Pinhero
Tks for your incredible packages in R I did my master in statistics (attached). I’m a big fan!
However I’m puzzled with several theoretical questions on some topic where I’m struggling; instead of luring for stat input I asks directly WIZARDS!:
Variograms (Cressie):P 52 PDF
I have done several variograms on my model residuals expecting flat line along (sill flat).However some patient are at sill some on the correlation path-slope.
Q:How to interpret? (Two class of patient with biophysical discerpancies?
Q:The smoother fitted in graph is the theoretical one (Theoretical variogram based on exp?spherical?)?? Or is it a simple smoother.
Q: Is it possible with variogram (within (patient and sampling error) cor + between from LMM variance) to forecast the best time for re-measure?
I.e in cholesterol study some authors demonstrated when intra- variability exceed between variability? So measuring on too short intervals has no value.But I don’t know how to proceed
Or do you had a good reference.?
Fiiting confindance bands on XB+ZU:
Q.I try to get con band for predictings patients trajectories. As they is no close form (at least very complex) is the better way to bootstrap some model and fit a bootstrap confint on the 1000 Fitted values? Or do you have a smplier function?
Q:If I should predict when time will be reached for a patient his Upper reference limit how do I have to proceed? (back reversing formula?)
Page 54 :patients prediction
Tks for your help in an old retrained statistician
NB Your contribution to staworld is fabulous and inspired me in my daily work since a year!
Veuillez recevoir mes sincères salutations ,
8 ch du Châno
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