R: Fit a Linear Model

ols.fit-methods {fastmatrix}

R Documentation

Fit a Linear Model

Fits a linear model, returning the bare minimum computations.

ols.fit.cg(x, y, tol = 1e-7, maxiter = 100)
ols.fit.chol(x, y)
ols.fit.qr(x, y)
ols.fit.svd(x, y)
ols.fit.sweep(x, y)

`x, y`	numeric vectors or matrices for the predictors and the response in a linear model. Typically, but not necessarily, `x` will be constructed by one of the fitting functions.
`tol`	tolerance for the conjugate gradients (`gc`) method. Default is `tol = 1e-7`.
`maxiter`	The maximum number of iterations for the conjugate gradients (`gc`) method. Defaults to 100.

The bare bones of an ols object: the coefficients, residuals, fitted values, and some information used by summary.ols.

set.seed(151)
n <- 100
p <- 2
x <- matrix(rnorm(n * p), n, p) # no intercept!
y <- rnorm(n)
z <- ols.fit.chol(x, y)
z

[Package fastmatrix version 0.4 Index]