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

Description Usage Arguments Value Examples

View source: R/clean_fit.R

Description

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

Usage

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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

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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))

WinVector/wrapr documentation built on Nov. 21, 2020, 8:31 p.m.