I think this might be a very basic question, but is there a simple way to characterise the relationships that a gam or lm model have identified? I am trying the create species distribution models based on climate, and want to know whether, for example, higher temperatures (one of the predictor variables) leads to a higher probability of species presence (dependent variable). Also, how can you quantify the relative contribution of each predictor variable to the final model?
Many thanks, James -- View this message in context: http://www.nabble.com/GAM-GLM-parameters-tf3525876.html#a9837219 Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@stat.math.ethz.ch 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.