reg_intervals: A convenience function for confidence intervals with...

In rsample: General Resampling Infrastructure

A convenience function for confidence intervals with linear-ish parametric models

Description

A convenience function for confidence intervals with linear-ish parametric models

Usage

reg_intervals(
  formula,
  data,
  model_fn = "lm",
  type = "student-t",
  times = NULL,
  alpha = 0.05,
  filter = term != "(Intercept)",
  keep_reps = FALSE,
  ...
)

Arguments

formula	An R model formula with one outcome and at least one predictor.
data	A data frame.
model_fn	The model to fit. Allowable values are "lm", "glm", "survreg", and "coxph". The latter two require that the survival package be installed.
type	The type of bootstrap confidence interval. Values of "student-t" and "percentile" are allowed.
times	A single integer for the number of bootstrap samples. If left NULL, 1,001 are used for t-intervals and 2,001 for percentile intervals.
alpha	Level of significance.
filter	A logical expression used to remove rows from the final result, or NULL to keep all rows.
keep_reps	Should the individual parameter estimates for each bootstrap sample be retained?
...	Options to pass to the model function (such as family for glm()).

Value

A tibble with columns "term", ".lower", ".estimate", ".upper", ".alpha", and ".method". If keep_reps = TRUE, an additional list column called ".replicates" is also returned.

References

Davison, A., & Hinkley, D. (1997). Bootstrap Methods and their Application. Cambridge: Cambridge University Press. doi:10.1017/CBO9780511802843

Bootstrap Confidence Intervals, https://rsample.tidymodels.org/articles/Applications/Intervals.html

See Also

int_pctl(), int_t()

Examples

set.seed(1)
reg_intervals(mpg ~ I(1 / sqrt(disp)), data = mtcars)

set.seed(1)
reg_intervals(mpg ~ I(1 / sqrt(disp)), data = mtcars, keep_reps = TRUE)

rsample documentation built on May 29, 2024, 11:03 a.m.