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bigFastlm

A reimplementation of the fastLm functionality of RcppEigen for big.matrix objects for fast out-of-memory linear model fitting

Build Status

OSBuild
Linux x86_64
Windows x86_64

Installation

Install using the devtools package (RcppEigen and bigmemory must be installed first as well):

devtools::install_github("jaredhuling/bigFastlm")

Usage

library(bigFastlm)
library(bigmemory)

nrows <- 50000
ncols <- 50
bkFile <- "bigmat.bk"
descFile <- "bigmatk.desc"
bigmat <- filebacked.big.matrix(nrow=nrows, ncol=ncols, type="double",
                                backingfile=bkFile, backingpath=".",
                                descriptorfile=descFile,
                                dimnames=c(NULL,NULL))

set.seed(123)
for (i in 1:ncols) bigmat[,i] = rnorm(nrows)*i

y <- rnorm(nrows) + bigmat[,1]

system.time(lmr1 <- bigLm(bigmat, y))

summary(lmr1)

predictions <- predict(lmr1, newdata = bigmat)

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Version

Install

install.packages('bigFastlm')

Monthly Downloads

2

Version

0.0.1

License

GPL (>= 2)

Maintainer

Jared Huling

Last Published

October 6th, 2016

Functions in bigFastlm (0.0.1)

bigLm

fast and memory efficient linear model fitting
predict.bigLm

Prediction method for bigLm fitted objects
bigLmPure

fast and memory efficient linear model fitting
%*%,big.matrix,vector-method

big.matrix prod
print.bigLm

print method for bigLm objects
summary.bigLm

summary method for bigLm fitted objects