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).
CONICET
Bvd. Brown s/nº.
(U9120ACV)Pto. Madryn
Chubut
Argentina
Tel: 54-2965/451301/451024/451375/45401 (Int:277)
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