I'm having hard time understanding the computation of degrees of freedom when runing nlme () on the following model:
   
  > formula(my data.gd)
dLt ~ Lt | ID
   
  TasavB<- function(Lt, Linf, K) (K*(Linf-Lt))
   
  my model.nlme <- nlme (dLt ~ TasavB(Lt, Linf, K),
  data = my data.gd,
  fixed = list(Linf ~ 1, K ~ 1), 
  start = list(fixed = c(70, 0.4)),
  na.action= na.include, naPattern = ~!is.na(dLt))
   
  > summary(my model.nlme)
Nonlinear mixed-effects model fit by maximum likelihood
  Model: dLt ~ TasavB(Lt, Linf, K) 
 Data: my data.gd 
       AIC      BIC    logLik 
  13015.63 13051.57 -6501.814
  Random effects:
 Formula: list(Linf ~ 1 , K ~ 1 )
 Level: ID
 Structure: General positive-definite
            StdDev   Corr 
    Linf 7.3625291 Linf  
       K 0.0845886 -0.656
Residual 1.6967358       
  Fixed effects: list(Linf + K ~ 1) 
        Value Std.Error   DF  t-value p-value 
Linf 69.32748 0.4187314  402 165.5655  <.0001
   K  0.31424 0.0047690 2549  65.8917  <.0001
  Standardized Within-Group Residuals:
      Min         Q1         Med        Q3      Max 
 -3.98674 -0.5338083 -0.02783649 0.5261591 4.750609
  Number of Observations: 2952
Number of Groups: 403 

  Why are the DF of Linf and K different? I would apreciate if you could point me to a reference.


Lic. Gabriela Escati Peñaloza
Biología y Manejo de Recursos Acuáticos
Centro Nacional Patagónico(CENPAT). 
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