fast.lm: no frills linear regression
In armstrtw/fast.lm: linear model and variations using Armadillo

Description Usage Arguments Value Author(s) See Also Examples

a no frills version of lm. designed to return only the coefficients and nothing else. (and potentially some basic stats in a future version)

1	fast.lm(A, x)

`A`	design matrix of dimension `n * p`.
`x`	vector of observations of length `n`, or a matrix with `n` rows.

the length p coefficient vector.

Whit Armstrong

lm the standard lm method.

NC <- 10
NR <- 1e5
A <- matrix(rnorm(NR*NC),nrow=NR,ncol=NC)
b <- rnorm(NR)
flm.time <- system.time(ans <- fast.lm(A,b))
lm.fit.time <- system.time(lm.ans <- as.vector(lm.fit(A,b)$coefficients))
cat("all.equal:", all.equal(ans,lm.ans),"\n")

bmark.times <- rbind(flm.time,
                     lm.fit.time,
                     lm.fit.time/flm.time)
print(bmark.times)
ans.compare <- cbind(ans,lm.ans)