fast_forward: Fast-forward step

In bigstep: Stepwise Selection for Large Data Sets

Fast-forward step

Description

Add variables to a model as long as they reduce the given criterion. Variables are searched according to candidates and every one which reduces the criterion is added (not necessarily the best one).

Usage

fast_forward(data, crit = bic, ..., maxf = 70)

Arguments

data	an object of class big.
crit	a function defining the model selection criterion. You can use your own function or one of these: bic, mbic, mbic2, aic, maic, maic2.
...	optional arguments to crit.
maxf	a numeric, a maximal number of variables in the final model.

Details

Type browseVignettes("bigstep") for more details.

Value

An object of class big.

Examples

set.seed(1)
n <- 30
p <- 10
X <- matrix(rnorm(n * p), ncol = p)
y <- X[, 2] + 2*X[, 3] - X[, 6] + rnorm(n)
d <- prepare_data(y, X)
fast_forward(d)

bigstep documentation built on May 31, 2023, 5:36 p.m.