Hi Everyone,
I often use the 'safe prediction' feature available through glm().
Now, I'm at a situation where I must use biglm:::bigglm.
## begin example
library(splines)
library(biglm)
ff <- log(Volume)~ns(log(Girth), df=5)
fit.glm <- glm(ff, data=trees)
fit.biglm <- bigglm(ff, data=trees)
predict(fit.glm, newdata=data.frame(Girth=2:5))
## -1.3161465 -0.2975659 0.4251285 0.9856938
predict(fit.biglm, newdata=data.frame(Girth=2:5))
## Error in predict(fit.biglm, newdata = data.frame(Girth = 2:5)) :
## no applicable method for "predict"
## end example
So, it is my understanding that there is no 'predict' method for
'bigglm' class. That suggests me that I need to create my own
prediction method, right? What would be an efficient way of making
these predictions that use ns() on a very large dataset?
My initial thought is that saving the Boundary.knots and knots, I
could create the linear predictor by chunks (and therefore get the
predictions). Is there a better way of doing this?
Thank you very much.
Benilton Carvalho
Department of Biostatistics
Bloomberg School of Public Health
Johns Hopkins University
