[R] offset in gam and spatial scale of variables

[Simon Wood]

> We are analizing the relationship between the abundance of groupers in line
> transects and some variables. We are using the quasipoisson distribution.
> Do we need to include the length of the transects as an offset if they all
> have the same length??
--- not just for fitting, I suppose: although I guess you may need some care 
in interpreting the units of the fitted model predictions, if you leave it 
out. 

> Also, can we include in the gam models variables that are measured at
> different spatial scales? We have done an analysis to see what variables
> are better for different sizes of buffers around the transect lines and
> some variables are better at different scales. Can we run the gam model
> with several explanatory variables if they are measured at different
> spatial scales?
--- Do you mean, for example, that that sea surface temperature was measured 
every in 10km grid squares by satellite, whereas salinity was measured every 
quarter nautical mile directly? 

--- If so, I think that you can use such data, but you  need a clear method 
for converting what is measured about the covariate to  a covariate value 
associated with each response measurement. As an example you might have 
salinity measures that are widely scattered, and do not coincide with the 
locations of response measurements. One option is to smooth or interpolate 
the salinity values, and use the resulting predicted salinities at each 
response datum location as covariates. Of course if you do this sort of thing 
it's important that only such predicted salinities are used for predicting 
from the model (i.e. not to switch to direct measurements of salinity for 
prediction)

best,
Simon

>
> Thanks,
>
> Lucia

-- 
> Simon Wood, Mathematical Sciences, University of Bath, Bath, BA2 7AY UK
> +44 1225 386603  www.maths.bath.ac.uk/~sw283