clean_fit_lm: Fit a stats::lm without carying back large structures.

In wrapr: Wrap R Tools for Debugging and Parametric Programming

Fit a stats::lm without carying back large structures.

Description

Please see https://win-vector.com/2014/05/30/trimming-the-fat-from-glm-models-in-r/ for discussion.

Usage

clean_fit_lm(
  outcome,
  variables,
  data,
  ...,
  intercept = TRUE,
  weights = NULL,
  env = baseenv()
)

Arguments

outcome	character, name of outcome column.
variables	character, names of varaible columns.
data	data.frame, training data.
...	not used, force later arguments to be used by name
intercept	logical, if TRUE allow an intercept term.
weights	passed to stats::glm()
env	environment to work in.

Value

list(model=model, summary=summary)

Examples

mk_data_example <- function(k) {
  data.frame(
    x1 = rep(c("a", "a", "b", "b"), k),
    x2 = rep(c(0, 0, 0, 1), k),
    y = rep(1:4, k),
    yC = rep(c(FALSE, TRUE, TRUE, TRUE), k),
    stringsAsFactors = FALSE)
}

res_lm <- clean_fit_lm("y", c("x1", "x2"),
                       mk_data_example(1))
length(serialize(res_lm$model, NULL))

res_lm <- clean_fit_lm("y", c("x1", "x2"),
                       mk_data_example(10000))
length(serialize(res_lm$model, NULL))

predict(res_lm$model,
        newdata = mk_data_example(1))

wrapr documentation built on Aug. 20, 2023, 1:08 a.m.