Hi, I am not sure it is the best to use a binomial distribution for a continuous bounded variable. A beta distribution would be more appropriate, although I don't know how to define one for the gam() function. On the other hand beta distribution is closely linked to the gamma distribution so maybe you can use it to define a beta family for the gam() function.
Some info about beta distribution: http://www.stat.purdue.edu/~jrnolan/portfolio/the_big_ten/beta.pdf Also, I am not very sure how you did a gam using binomial family without having your response data converted in 0 and 1. Didn't you get a warning saying that: Warning messages: 1: In eval(expr, envir, enclos) ... : non-integer #successes in a binomial glm! Maybe you can contact the author of the mgcv package. I am curious to see his response. Sorry I cannot help much more, Monica ------------------------------------------------------------------------------------------------------------------------ Message: 96 Date: Thu, 21 Aug 2008 00:53:52 +0200 From: Marina Laborde Subject: [R] GAM-binomial logit link To: Message-ID: Content-Type: text/plain Dear all, I'm using a binomial distribution with a logit link function to fit a GAM model. I have 2 questions about it. First i am not sure if i've chosen the most adequate distribution. I don't have presence/absence data (0/1) but I do have a rate which values vary between 0 and 1. This means the response variable is continuous even if within a limited interval. Should i use binomial? Secondly, in the numerical output i get negative values of UBRE score. I would like to know if one should consider the lowest absolute value or the lowest real value to select the best model. Thank you in advance for your help. Marina _________________________________________________________________ yahoo_082008 ______________________________________________ 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.
