Hi, I am fitting two models, a generalized linear model and a generalized additive model, to the same data. The R-Help tells that "A generalized additive model (GAM) is a generalized linear model (GLM) in which the linear predictor is given by a user specified sum of smooth functions of the covariates plus a conventional parametric component of the linear predictor." I am fitting the GAM without smooth functions and would have expected the parameter estimates to be equal to the GLM.
I am fitting the following model: reg.glm=glm(YES~factor(RoundStart)+DEP+SPD+S.S+factor(LOST),family=binomial( link="probit")) reg.gam=gam(YES~factor(RoundStart)+DEP+SPD+S.S+factor(LOST),family=binomial( link="probit")) DEP, SPD, S.S, and LOST are invariant across the observations within the same RoundStart. Therefore, I would expect to get NAs for these parameter estimates. I get NAs in GLM, but I get estimates in GAM. Can anyone explain why that is? Thanks much, Daniel ------------------------- cuncta stricte discussurus ______________________________________________ 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.
