nlminb problem, convergence error code = 1 message = iteration limit reached without convergence (10)

Question

I am trying to find a best model fitting on my data using library(nlme) and lme function in R. Here is my model when the slope is fixed:

FixedRopeLength <- lme(EnergyCost~ RopeLength, 
  data = data, 
  random=~1|Subject, method = "ML")
summary(FixedRopeLength)

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To see whether a random slope provides a better model than a fixed slope, I let the slope to vary across Subject as follows:

RandomRopeLength <- lme(EnergyCost~RopeLength,
 data = data, 
 random=~RopeLength|Subject, method = "ML")
summary(RandomRopeLength)

---

However, I got this error:

Error in lme.formula(EnergyCost ~ RopeLength, data = data, random = ~RopeLength | : nlminb problem, convergence error code = 1
message = iteration limit reached without convergence (10)

Any solution??

Answer 1

Thank you so much for your help. Your code worked. I only needed to justify your code based on lme function. Here is the code which can be used for aforementioned error:

RandomRopeLength<-lme(EnergyCost~RopeLength, data = data, random=~RopeLength|Subject, method = "ML", control =list(msMaxIter = 1000, msMaxEval = 1000)) summary(RandomRopeLength)

Thanks!

Answer 2

?lme shows that there is a control argument, which redirects you to ?lmerControl, which gives you

msMaxIter: maximum number of iterations for the optimization step inside the ‘lme’ optimization. Default is ‘50’.

and

msMaxEval: maximum number of evaluations of the objective function permitted for nlminb. Default is ‘200’.

These correspond to eval.max and iter.max from ?nlminb. Since I'm not sure which of these is the problem, I would re-run the model with

control = lmeControl(msMaxIter = 1000, msMaxEval = 1000)

However, I'll warn you that once you have a problem that experiences numerical problems with the default parameter settings, adjusting the parameter settings may just lead to other problems farther down the line ...