> 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 ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.