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.