Does anybody know what are the attributes of a glm fit object that will allow
the "predict call" to produce an se.fit?
I am deleting most of the attributes as the size of the final object is 5Gb and
I want to reduce it to under 20Mb, but that causes as error when I ask for an
se.fit .
mod.b$fitted.values <- 1:10
mod.b$prior.weights <- 1:10
mod.b$data <-mod.b$data[1:10,]
mod.b$residuals <- 1:10
mod.b$linear.predictors <- 1:10
mod.b$qr$qr <- mod.b$qr$qr[1:10,]
mod.b$effects <- mod.b$effects[1:100]
mod.b$weights <- mod.b$weights[1:100]
mod.b$model <- mod.b$model[1:10,]
mod.b$y <- mod.b$y[1:10]
p1 <- predict(mod.b,new=newdata,type="link",se.fit=T)
Error in Qr$qr[p1, p1, drop = FALSE] : subscript out of bounds
I believe the covariance matrix of the coefficients is all that should be
needed and that is quite small. However, the covariance matrix is not an
attribute of the model object.
Thanks everybody.
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