Hi Noah GAM models were developed to assess the functional form of the relationship of continuous predictor variables to the response, so weren't really meant to handle factor variables as predictor variables. GAMs are of the form E(Y | X1, X2, ...) = So + S(X1) + S(X2) + ... where S(X) is a smooth function of X.
Hence you might want to rethink why you'd want a factor variable as a predictor variable in a GAM. This is why the gam machinery doesn't just do the factor conversion to indicator variables as is done in lm. HTH Steven McKinney ________________________________________ From: r-help-boun...@r-project.org [r-help-boun...@r-project.org] On Behalf Of Noah Silverman [n...@smartmediacorp.com] Sent: March 19, 2010 12:54 PM To: r-help@r-project.org Subject: [R] Factor variables with GAM models I'm just starting to learn about GAM models. When using the lm function in R, any factors I have in my data set are automatically converted into a series of binomial variables. For example, if I have a data.frame with a column named color and values "red", "green", "blue". The lm function automatically replaces it with 3 variables colorred, colorgreen, colorblue which are binomial {0,1} When I use the gam function, R doesn't do this so I get an error. 1) Is there a way to ask the gam function to do this conversion for me? 2) If not, is there some other tool or utility to make this data transformation easy? 3) Last option - can I use lm to transform the data and then extract it into a new data.frame to then pass to gam? Thanks!!! ______________________________________________ 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. ______________________________________________ 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.