[R] nlme iteration process, few questions

[Vaidotas Zemlys]

Hi all,

Recently I started using nlme intensively, and since it is all new for
me, I have some questions. I am running nlme with
control=list(verbose=TRUE) and during one lengthy fitting, I started
watching the output for some clues, how to speed up the process. I
noticed that in one case, the iteration process is alternating between
two solutions. Here is an output of 5 iterations, after which I
stopped the calculation:

**Iteration 22
LME step: Loglik: -1580.5 , nlm iterations: 50
reStruct  parameters:
        id1         id2         id3         id4         id5         id6
 -2.6387745   5.7964164   3.4153271   4.1734349  48.7541909  -0.1250377
        id7         id8         id9        id10
-36.7011651  30.1780697 -56.0266217 127.3234221

PNLS step: RSS =  137743.3
 fixed effects:24.0656  0.105708  -2.86501  0.542384
 iterations: 7

Convergence:
    fixed  reStruct
0.1353935 3.3655468

**Iteration 23
LME step: Loglik: -1579.346 , nlm iterations: 50
reStruct  parameters:
       id1        id2        id3        id4        id5        id6        id7
 -2.285671   6.380246   3.583532   4.248227  -1.398577  -1.318335 -47.773224
       id8        id9       id10
 12.834766 -63.669545 136.063383

PNLS step: RSS =  151492.2
 fixed effects:20.8075  0.105065  -2.85908  0.544615
 iterations: 7

Convergence:
    fixed  reStruct
0.1565794 1.5396836

**Iteration 24
LME step: Loglik: -1580.500 , nlm iterations: 50
reStruct  parameters:
        id1         id2         id3         id4         id5         id6
 -2.6387708   5.7964464   3.4153368   4.1734411  48.7509855  -0.1246523
        id7         id8         id9        id10
-36.7012641  30.1788064 -56.0254345 127.3242285

PNLS step: RSS =  137743.5
 fixed effects:24.0665  0.105706  -2.86503  0.542385
 iterations: 7

Convergence:
    fixed  reStruct
0.1354136 3.3647287

**Iteration 25
LME step: Loglik: -1579.346 , nlm iterations: 50
reStruct  parameters:
       id1        id2        id3        id4        id5        id6        id7
 -2.285674   6.380234   3.583527   4.248225  -1.399981  -1.318104 -47.772885
       id8        id9       id10
 12.835424 -63.669219 136.063111

PNLS step: RSS =  151495.6
 fixed effects:20.8062  0.105066  -2.85907  0.544616
 iterations: 7

Convergence:
    fixed  reStruct
0.1566962 1.5398072

**Iteration 26
LME step: Loglik: -1580.500 , nlm iterations: 50
reStruct  parameters:
        id1         id2         id3         id4         id5         id6
 -2.6387698   5.7964218   3.4153246   4.1734379  48.7501373  -0.1249832
        id7         id8         id9        id10
-36.7020319  30.1775554 -56.0315196 127.3225180

PNLS step: RSS =  137744.8
 fixed effects:24.066  0.105707  -2.86501  0.542384
 iterations: 7

Convergence:
    fixed  reStruct
0.1354528 3.3650687


Is there any particular strategy I can pursue in such case? Besides
the usual ones: changing the starting values, changing the model,
using different scaling. I am not familiar with inner workings of nlme
algorithm, maybe this an indication of some known problem?

Thanks for all answers.

Vaidotas Zemlys
--
Doctorate student, Vilnius University
http://www.mif.vu.lt/katedros/eka/katedra/zemlys.php