Hello,
I am a bit confused about gamm in mgcv. Consulting Wood (2006) or Ruppert et
al. (2003) hasn't taken away my confusion.
In this code from the gamm help file:
b2<-gamm(y~s(x0)+s(x1)+s(x2)+s(x3),family=poisson,random=list(fac=~1))
Am I correct in assuming that we have a random intercept here....but that the
amount of smoothing is also changing per level of the factor?? Or is it only
the intercept that is changing?
And where can I find some explanation on the magic output below?
Thanks
Piet
summary(b2$lme)
Random effects:
Formula: ~Xr.1 - 1 | g.1
Structure: pdIdnot
Xr.11 Xr.12 Xr.13 Xr.14 Xr.15 Xr.16 Xr.17 Xr.18
StdDev: 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679 1.680679
Formula: ~Xr.2 - 1 | g.2 %in% g.1
Structure: pdIdnot
Xr.21 Xr.22 Xr.23 Xr.24 Xr.25 Xr.26 Xr.27 Xr.28
StdDev: 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598 1.57598
Formula: ~Xr.3 - 1 | g.3 %in% g.2 %in% g.1
Structure: pdIdnot
Xr.31 Xr.32 Xr.33 Xr.34 Xr.35 Xr.36 Xr.37 Xr.38
StdDev: 20.06377 20.06377 20.06377 20.06377 20.06377 20.06377 20.06377 20.06377
Formula: ~Xr.4 - 1 | g.4 %in% g.3 %in% g.2 %in% g.1
Structure: pdIdnot
Xr.41 Xr.42 Xr.43 Xr.44 Xr.45
StdDev: 0.0001063304 0.0001063304 0.0001063304 0.0001063304 0.0001063304
Xr.46 Xr.47 Xr.48
StdDev: 0.0001063304 0.0001063304 0.0001063304
Formula: ~1 | fac %in% g.4 %in% g.3 %in% g.2 %in% g.1
(Intercept) Residual
StdDev: 0.6621173 1.007227
Variance function:
Structure: fixed weights
Formula: ~invwt
Fixed effects: y.0 ~ X - 1
Value Std.Error DF t-value p-value
X(Intercept) 2.0870364 0.3337787 392 6.252755 0.0000
Xs(x0)Fx1 -0.0000325 0.1028794 392 -0.000316 0.9997
Xs(x1)Fx1 0.3831694 0.0957323 392 4.002509 0.0001
Xs(x2)Fx1 1.4584330 0.3909237 392 3.730736 0.0002
Xs(x3)Fx1 -0.0123951 0.0143162 392 -0.865809 0.3871
Correlation:
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