Hi all,
I am interested in modeling total fish catch using gam in mgcv to model simple
random effects for individual vessels (that make repeated trips over time in
the fishery). I have 98 subjects, so I thought I would use gam instead of gamm
to model the random effects. My model is:
modelGOM <- gam(TotalFish ~ factor(SetYear) + factor(SetMonth) +
factor(TimePeriod) + s(SST) + s(VesselID, bs = "re", by = dum) + s(Distance,
by = TimePeriod) + offset(log(HooksSet)), data = GOM, family = tw(), method =
"REML")
I have coded the random effect with bs = "re" and by = dum (which should allow
me to predict with the vessel effects at their predicted values or zero), where
"dum" is a vector of 1.
The model runs, but I am having problems predicting.
grid.bin.GOM_A_Swordfish <-
data.frame("Distance"=seq(min(GOM$Distance),max(GOM$Distance),length =
100),#range of distances over which to predict
"SetYear" = '2006',
"SetMonth" = '6',
"TimePeriod" = 'A',
"SST" = mean(GOM$SST),
"VesselID" = 'MEDIHO', #I picked one of the
levels of the random effect, Vessel MEDIHO
"dum" = '0', #to predict without vessel effect
"HooksSet" = mean(GOM$HooksSet))
pred_GOM_A_Swordfish <- predict(modelGOM, grid.bin.GOM_A_Swordfish, type =
"response", se = T)
The error that I'm getting is:
Error in Predict.matrix.tprs.smooth(object, dk$data) :
NA/NaN/Inf in foreign function call (arg 1)
In addition: Warning message:
In Ops.factor(xx, object$shift[i]) : - not meaningful for factors
I think this is being called because VesselID is a factor, but I'm using it a
smooth for the random effects. Can you provide any advice on how to predict
this model without the VesselID term (but still include it in fitting)?
Thanks!
Meagan
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