On Thu, 30 Sep 2004, Christoph Lehmann wrote:
many thanks I did it the following way, based on Thomas' suggestion
There was a reason why I didn't call the function predict.glm.fit: it isn't a method for predict. You will be calling it directly, rather than via predict as you should for a method.
-thomas
predict.glm.fit<-function(glmfit, newmatrix){ newmatrix<-cbind(1,newmatrix) coef <- rbind(1, as.matrix(glmfit$coef)) eta <- as.matrix(newmatrix) %*% as.matrix(coef) exp(eta)/(1 + exp(eta)) }
cheers
christoph
Thomas Lumley wrote:On Wed, 29 Sep 2004, Christoph Lehmann wrote:
Hi
when I fit a glm by
glm.fit(x,y,family = binomial()) and then try to use the object for prediction of newdata by:
predict.glm(object, newdata)
I get the error:
Error in terms.default(object) : no terms component
I know I can use glm() and a formula, but for my case I prefer glm.fit(x,y)...
Well, you can't use predict.glm that way. As the function name suggests, it is a predict method for objects of class "glm", which in your case you do not have.
There are two reasons why it won't work. For type="terms" the formula is needed to identify terms, and for any type of prediction the formula is needed to convert the data frame newdata into a model matrix.
You would need to write a function where the new data was a model matrix. If you only need point predictions then
predict_glm_fit<-function(glmfit, newmatrix, addintercept=TRUE){ if (addintercept) newmatrix<-cbind(1,newmatrix) eta<-glmfit$coef %*% newmatrix family$linkinv(eta) }
would work.
-thomas
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Thomas Lumley Assoc. Professor, Biostatistics [EMAIL PROTECTED] University of Washington, Seattle
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