Dear all,

I'm using predict.gam (mgcv package) to predict count data (y) from line
transect to a regular grid. My model have this form:

y=offset(log(x1*0.6))+s(x2)+s(
x3)+s(x4), family=quasipoisson,...

the offset is the area covered by a portion of a transect line
(length(x1)*observation distance(0.6)). The length is almost always 1 km
since I splitted the transect in 1 km segments. I have different length
value only for the segments at the end of the transects. The observation
distance is always the same.

To predict on a regular grid (2 km * 2 km), using predict.gam, should I use
the area of each cell or use 1 km for the offset variable x1? I obtained
more logical result with x1=1 km in my prediction grid.

Thanks

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