ols_step_all_possible: All possible regression

In olsrr: Tools for Building OLS Regression Models

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, ...)

## Default S3 method:
ols_step_all_possible(model, max_order = NULL, ...)

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

Arguments

model	An object of class lm.
...	Other arguments.
max_order	Maximum subset order.
x	An object of class ols_step_all_possible.
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:

mindex	model index
n	number of predictors
predictors	predictors in the model
rsquare	rsquare of the model
adjr	adjusted rsquare of the model
rmse	root mean squared error 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
msep	estimated MSE of prediction, assuming multivariate normality
fpe	final prediction error
apc	amemiya prediction criteria
hsp	hocking's Sp

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)

# maximum subset
model <- lm(mpg ~ disp + hp + drat + wt + qsec, data = mtcars)
ols_step_all_possible(model, max_order = 3)

olsrr documentation built on May 29, 2024, 12:35 p.m.