Re: [R] Proper syntax for using varConstPower in nlme
On Fri, Oct 16, 2009 at 3:56 PM, Michael A. Gilchrist mi...@utk.edu wrote: Hi Dieter, Thanks for the reply. I had played with the initial conditions, but apparently not enough. I finally found some that avoided the singularity issue. Many thanks. More generally, I went over the documentation yet again in PB and I still find it a bit confusing. They talk about using form = ~fitted(.) when discussing varPower, but the rest of the documentation seems to suggest that form = ~... should be used to indicate which covariate you assume the variance changes with. Could you or someone else provide some clarification? I don't have PB in front of me, but see the 'form' agument definition on the help page for any of the variance structures depending on a covariate (varPower, varConstPower or varExp). The ~fitted(.) and ~resid(.) notation specify that you would like the variance covariate to be a function of the model being fit (the fitted values or residuals), in which case the variance parameter \delta and the model body are estimated iteratively. Conversely, if you specify a constant variance covariate such as ~age, there is no need for updating of the variance covariate during optimization. hth, Kingsford Jones Thanks. Mike On Fri, 16 Oct 2009, Dieter Menne wrote: Michael A. Gilchrist wrote: - nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 You could use varPower(form=~fitted()) (the default, also varPower()). In my experience this runs into some limitation quickly with nlme, because some boundary conditions make convergence fail. Try varPower(fixed = 0.5) first and play with the number. You should only use varConstPower when you have problems with values that cover a large range, coming close to zero, which could make varPower go havoc. Always do a plot of the result; the default plot gives you residual, and some indication how to proceed. Dieter -- View this message in context: http://www.nabble.com/Proper-syntax-for-using-varConstPower-in-nlme-tp25914277p25927578.html Sent from the R help mailing list archive at Nabble.com. __ 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. __ 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. __ 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.
Re: [R] Proper syntax for using varConstPower in nlme
Michael A. Gilchrist wrote: - nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 You could use varPower(form=~fitted()) (the default, also varPower()). In my experience this runs into some limitation quickly with nlme, because some boundary conditions make convergence fail. Try varPower(fixed = 0.5) first and play with the number. You should only use varConstPower when you have problems with values that cover a large range, coming close to zero, which could make varPower go havoc. Always do a plot of the result; the default plot gives you residual, and some indication how to proceed. Dieter -- View this message in context: http://www.nabble.com/Proper-syntax-for-using-varConstPower-in-nlme-tp25914277p25927578.html Sent from the R help mailing list archive at Nabble.com. __ 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.
Re: [R] Proper syntax for using varConstPower in nlme
Hi Dieter, Thanks for the reply. I had played with the initial conditions, but apparently not enough. I finally found some that avoided the singularity issue. Many thanks. More generally, I went over the documentation yet again in PB and I still find it a bit confusing. They talk about using form = ~fitted(.) when discussing varPower, but the rest of the documentation seems to suggest that form = ~... should be used to indicate which covariate you assume the variance changes with. Could you or someone else provide some clarification? Thanks. Mike On Fri, 16 Oct 2009, Dieter Menne wrote: Michael A. Gilchrist wrote: - nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 You could use varPower(form=~fitted()) (the default, also varPower()). In my experience this runs into some limitation quickly with nlme, because some boundary conditions make convergence fail. Try varPower(fixed = 0.5) first and play with the number. You should only use varConstPower when you have problems with values that cover a large range, coming close to zero, which could make varPower go havoc. Always do a plot of the result; the default plot gives you residual, and some indication how to proceed. Dieter -- View this message in context: http://www.nabble.com/Proper-syntax-for-using-varConstPower-in-nlme-tp25914277p25927578.html Sent from the R help mailing list archive at Nabble.com. __ 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. __ 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.
[R] Proper syntax for using varConstPower in nlme
Hello, Excuse me for posting two questions in one day, but I figured it would be better to ask my questions in separate emails. I will again give the caveat that I'm not a statistician by training, but have a fairly decent understanding of probability and likelihood. As before, I'm trying to fit a nonlinear model to a dataset which has two main factors using nlme. Within the dataset there are two Type categories and four Tissue categories, thus giving me 8 datasets in total. The dataset is in a groupedData object with formula= Count ~ Time|Type/Tissue and there are three basic model parameters that I am trying to fit: T0, aN, and aL. Calling nlsList gives -- nlsList(Count ~ quad.PBMC.model(aL, aN, T0), data = tissueData, start = list(T0 = 1000, aN = exp(-2), aL = exp(-2))) Call: Model: Count ~ quad.PBMC.model(aL, aN, T0) | Type/Tissue Data: tissueData Coefficients: T0 aN aL Naive/CLN1530.0088 0.26508876 0.04730525 . . . Memory/IngLN 2114.1868 0.05298126 0.12795589 Memory/MLN 1050.0811 0.02277018 0.13560749 Degrees of freedom: 96 total; 72 residual Residual standard error: 271.4194 - I find that T0 varies greatly with each treatment, so I'm going to leave that alone for now. However, aN and aL values don't seem to vary w/in a Type or between Types. As a result, I would like a mixed effects model using nlme. Further, looking at the residuals, I find that they are heteroscedastic. As a result, I would like to try and model the variance in the data using varConstPowerFun within nlme. I've been trying to understand how to use this option by reading Pinheiro and Bates's book on mixed effects models. Based on this, I've tried using the syntax, - nlme(Count ~ quad.PBMC.model(aL, aN, T0), + data = tissueData, + weights = varConstPower(form =~ Count), + start = list( fixed = c(rep(1000, 8), -2, -2) ), + fixed = list(T0 ~ TypeTissue-1, aL ~ 1, aN ~ 1), + random = aL + aN ~ 1|Tissue + ) Error in MEestimate(nlmeSt, grpShrunk) : Singularity in backsolve at level 0, block 1 - The above command clearly this doesn't work, but if I comment out the weights = ... line, it executes with no problem. I'd greatly appreciate any guidance on how to properly set up varConstPower. Sincerely, Mike - Department of Ecology Evolutionary Biology 569 Dabney Hall University of Tennessee Knoxville, TN 37996-1610 phone:(865) 974-6453 fax: (865) 974-6042 web: http://eeb.bio.utk.edu/gilchrist.asp __ 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.
