[R] lme, best model without convergence

[Spencer Graves]

lmeControl               package:nlme               R Documentation

Control Values for lme Fit

Description:

      The values supplied in the function call replace the defaults and
      a list with all possible arguments is returned. The returned list
      is used as the 'control' argument to the 'lme' function.
##################

Note the last sentence.  Now consider the following example, combining 
modifications of your example with the example from "?lme":

 > lmeCtlList <-
+ lmeControl(maxIter=2,
+            msMaxIter=3, tolerance=1e-4, niter=4,
+ msTol=1e-5, nlmStepMax=5,
+  ,msVerbose=TRUE
+  ,returnObject=TRUE
+ )
 >
 >      fm1. <- lme(distance ~ age, data = Orthodont,
+                  control=lmeCtlList) # random is ~ age
   0      318.310: -0.202572 0.0501133  2.17193
   1      318.297: -0.202071 0.0662548  2.16740
   2      318.286: -0.207284 0.0593805  2.15302
   3      318.257: -0.215916 0.0783916  2.12677
   3      318.257: -0.215916 0.0783916  2.12677
Error in lme.formula(distance ~ age, data = Orthodont, control = 
lmeCtlList) :
	iteration limit reached without convergence (9)
 > fm1.
Linear mixed-effects model fit by REML
   Data: Orthodont
   Log-restricted-likelihood: -221.3183
   Fixed: distance ~ age
(Intercept)         age
  16.7611111   0.6601852

Random effects:
  Formula: ~age | Subject
  Structure: General positive-definite
             StdDev    Corr
(Intercept) 2.3270360 (Intr)
age         0.2264279 -0.609
Residual    1.3100396

Number of Observations: 108
Number of Groups: 27
 >
	  Hope this helps.
	  Spencer Graves
p.s.  First thanks for this example.  I didn't know until I read your 
question that one could actually get lme to return something when it 
didn't converge.  Second, you might have gotten a quicker reply if you 
had included a simple, self-contained example, as suggested in the 
posting guide! "www.R-project.org/posting-guide.html".  Instead, since I 
didn't know the answer, I had to invent one.  If your example had been 
self contained, you might have gotten an earlier reply from someone who 
didn't have the time or inclination to invent an example like I did but 
who might have otherwise been able to solve the problem.

Thomas Wutzler wrote:
> Dear R-help list readers,
> 
> I am fitting mixed models with the lme function of the nlme package.
> If I get convergence depends on how the method (ML/REM) and which (and 
> how much) parameters will depend randomly on the cluster-variable.
> 
> How get the bist fit without convergence?
> 
> 
> 
> 
> I set the parameters msVerbose and returnObject to TRUE:
> 
> lmeControl(maxIter=50000, msMaxIter=200, tolerance=1e-4, niter=50, 
> msTol=1e-5, nlmStepMax=500, 	
> 	,msVerbose=TRUE
> 	,returnObject=TRUE
> )
> 
> However, the lme-functions does not produce verbose output, nor does it 
> return the best fit if lme is not converging.
> It returns only an error:
> Error in lme.formula(y ~ lndbh + I(lndbh^2) + lnh + I(lnh^2), random = 
> ~lndbh +  :
>          iteration limit reached without convergence (9)
> 
> 
> 
> Best regards
> Thomas
> 
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