[R] NLME regression with weights, syntax in r

[LEPREVOST Florian (SNCF / DIR TECHNOLOGIES INNOVATION ET PROJETS GROUPE / IR DIR RECHERCHE -MEV)]

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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