Bounded memory linear regression
bigglm.ffdf creates a generalized linear model object that uses only p^2 memory for p variables. It uses the biglm package and is a simple wrapper to allow to work with an ffdf as input data. Make sure that package is loaded.
bigglm.ffdf(formula, data, family = gaussian(), ..., chunksize = 5000)
formula |
a model formula |
data |
an object of class ffdf |
family |
A glm family object |
... |
other parameters passed on to bigglm. See the biglm package: |
chunksize |
Size of chunks for processing the ffdf |
An object of class bigglm. See the bigglm package for a description: bigglm
## Not run: library(biglm) library(ff) data(trees) x <- as.ffdf(trees) a <- bigglm(log(Volume)~log(Girth)+log(Height), data=x, chunksize=10, sandwich=TRUE) summary(a) b <- bigglm(log(Volume)~log(Girth)+log(Height)+offset(2*log(Girth)+log(Height)), data=x, chunksize=10, sandwich=TRUE) summary(b) ## End(Not run)
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