[R] NLME regression with weights, syntax in r
Bert Gunter
bgunter@4567 @end|ng |rom gm@||@com
Sun Oct 30 15:16:32 CET 2022
1. No data, so may be impossible to help. Can you provide a minimal REPREX?
2. But probably better posted on r-sig-mixed-models anyway if you don't get
a useful answer here.
Cheers,
Bert
On Sun, Oct 30, 2022 at 3:20 AM LEPREVOST Florian (SNCF / DIR TECHNOLOGIES
INNOVATION ET PROJETS GROUPE / IR DIR RECHERCHE -MEV) <f.leprevost using sncf.fr>
wrote:
> Hi all,
>
> I found this (very) old post which had a similar problem but went without
> an answer (https://stat.ethz.ch/pipermail/r-help/2004-October/058325.html)
>
> I am trying to fit a power curve to model some observations in an nlme.
> However, I know some observations to be less reliable than others
> (reliability of each OBSID reflected in the WEIV in the dummy data),
> relatively independent of variance, and I quantified this beforehand and
> wish to include it as weights in my model. Moreover, I know a part of my
> variance is correlated with my independent variable so I cannot use
> directly the variance as weights.
>
> This is my model:
>
> coeffs_start = lm(log(DEPV)~log(INDV),
> filter(testdummy10,DEPV!=0))$coefficients
>
>
>
> nlme_fit <- nlme(DEPV ~ a*INDV^b,
>
> data = testdummy10,
>
> fixed=a+b~ 1,
>
> random = a~ 1,
>
> groups = ~ PARTID,
>
> start = c(a=exp(coeffs_start[1]), b=coeffs_start[2]),
>
> verbose = F,
>
> method="REML",
>
> weights=varFixed(~WEIV))
>
> This is some sample dummy data (I know it is not a great fit but it's fake
> data anyway) :
> https://github.com/FlorianLeprevost/dummydata/blob/main/testdummy10.csv
>
> This runs well without the "weights" argument, but when I add it I get
> this error and I am not sure why because I believe it is the correct syntax:
>
> Error in recalc.varFunc(object[[i]], conLin) :
>
> dims [product 52] do not match the length of object [220]
>
> In addition: Warning message:
>
> In conLin$Xy * varWeights(object) :
>
> longer object length is not a multiple of shorter object length
>
> Thanks in advance!
>
>
>
> Best
>
> Florian
>
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