On Wed, 2 Jan 2008, Daniel Malter wrote: > 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.
So your design matrix is rank-deficient and there is an identifiability problem. > I get NAs in GLM, but I get estimates in GAM. Can anyone explain > why that is? Because there is more than one way to handle rank deficiency. There are two different 'gam' functions in contributed packages for R (and none in R itself), so we need more details: see the footer of this message. In glm() the NA estimates are treated as zero for computing predictions. > Thanks much, > Daniel > > 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. -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ 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.
