olsrr: ols_step_all_possible – R documentation

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ols_step_all_possible

All possible regression

Description

Fits all regressions involving one regressor, two regressors, three regressors, and so on. It tests all possible subsets of the set of potential independent variables.

Usage

ols_step_all_possible(model, ...)

## S3 method for class 'ols_step_all_possible'
plot(x, model = NA, print_plot = TRUE,
  ...)

Arguments

`model`	An object of class `lm`.
`...`	Other arguments.
`x`	An object of class `ols_best_subset`.
`print_plot`	logical; if `TRUE`, prints the plot else returns a plot object.

Value

ols_step_all_possible returns an object of class "ols_step_all_possible". An object of class "ols_step_all_possible" is a data frame containing the following components:

`n`	model number
`predictors`	predictors in the model
`rsquare`	rsquare of the model
`adjr`	adjusted rsquare of the model
`predrsq`	predicted rsquare of the model
`cp`	mallow's Cp
`aic`	akaike information criteria
`sbic`	sawa bayesian information criteria
`sbc`	schwarz bayes information criteria
`gmsep`	estimated MSE of prediction, assuming multivariate normality
`jp`	final prediction error
`pc`	amemiya prediction criteria
`sp`	hocking's Sp

Deprecated Function

ols_all_subset() has been deprecated. Instead use ols_step_all_possible().

References

Mendenhall William and Sinsich Terry, 2012, A Second Course in Statistics Regression Analysis (7th edition). Prentice Hall

Examples

model <- lm(mpg ~ disp + hp, data = mtcars)
k <- ols_step_all_possible(model)
k

# plot
plot(k)

olsrr

Tools for Building OLS Regression Models

v0.5.3

MIT + file LICENSE

Authors

Aravind Hebbali [aut, cre]

Initial release