I adjusted a couple of models with different packages and their respective roles
I think these models are equivalent, ie they have the same fixed and random structures
 
exp.nlme<- nlme (dL~expT(largo, IncM,k),
     data = dL.gdOK,
     fixed = IncM +k~ 1,
     random= IncM+k~1,
     start = list(fixed = c(11.2,0.047)))
 
exp.nlmer2<-nlmer(dL~expT(largo, IncM,k)~(IncM+k|Codigo), dL.gdOK,
    start=c(IncM=11.2,k=0.047)) 
 
However, the output shows different values ​​for: estimates of fixed and random effects, variances and standard deviations of random effects, log-likelihoods…
 
> exp.nlme
Nonlinear mixed-effects model fit by maximum likelihood
  Model: dL ~ expT(largo, IncM, k) 
  Data: dL.gdOK 
  Log-likelihood: -2559.485
  Fixed: IncM + k ~ 1 
       IncM           k 
11.81793370  0.04770045 
 
Random effects:
 Formula: list(IncM ~ 1, k ~ 1)
 Level: Codigo
 Structure: General positive-definite, Log-Cholesky parametrization
         StdDev     Corr
IncM     5.17079862 IncM
k        0.01189968 0.6 
Residual 0.95701497     
 
Number of Observations: 1677
Number of Groups: 118
 
 
> exp.nlmer2
Nonlinear mixed model fit by the Laplace approximation 
Formula: dL ~ expT(largo, IncM, k) ~ (IncM + k | Codigo) 
   Data: dL.gdOK 
  AIC  BIC logLik deviance
 2052 2085  -1020     2040
Random effects:
 Groups   Name Variance   Std.Dev. Corr  
 Codigo   IncM 2.3700e+01 4.868270       
          k    1.2203e-04 0.011047 0.543 
 Residual      9.2676e-01 0.962685       
Number of obs: 1677, groups: Codigo, 118
 
Fixed effects:
      Estimate Std. Error t value
IncM 12.108597   0.489472   24.74
k     0.049541   0.001274   38.87
 
Correlation of Fixed Effects:
  IncM 
k 0.600
 
Could someone explain to me why these differences occur?
Could anyone tell me what causes these differences?
I have read enough material on nonlinear mixed effects but can not find the answer to my problem.
Cheers
Gabriela

Gabriela Escati Peñaloza
Centro Nacional Patagónico(CENPAT). 
CONICET
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(U9120ACV)Pto. Madryn 
Chubut
Argentina

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