summary method for class ".lm.fit".. It's 200 times faster than traditional lm.
Usage
summary_lm(obj, ...)
Value
a p x 4 matrix with columns for the estimated coefficient, its standard error,
t-statistic and corresponding (two-sided) p-value. Aliased coefficients are omitted.
set.seed(129)
n <- 100
p <- 2
X <- matrix(rnorm(n * p), n, p) # no intercept!y <- rnorm(n)
obj <- .lm.fit (x = cbind(1, X), y = y)
info <- summary_lm(obj)