ols_step_backward_aic {olsrr}

Stepwise AIC backward regression

Description

Build regression model from a set of candidate predictor variables by removing predictors based on akaike information criterion, in a stepwise manner until there is no variable left to remove any more.

Usage

ols_step_backward_aic(model, ...)

## Default S3 method:
ols_step_backward_aic(
  model,
  include = NULL,
  exclude = NULL,
  progress = FALSE,
  details = FALSE,
  ...
)

## S3 method for class 'ols_step_backward_aic'
plot(x, print_plot = TRUE, details = TRUE, digits = 3, ...)

Arguments

model

An object of class lm; the model should include all candidate predictor variables.

...

Other arguments.

include

Character or numeric vector; variables to be included in selection process.

exclude

Character or numeric vector; variables to be excluded from selection process.

progress

Logical; if TRUE, will display variable selection progress.

details

Logical; if TRUE, will print the regression result at each step.

x

An object of class ols_step_backward_*.

print_plot

logical; if TRUE, prints the plot else returns a plot object.

digits

Number of decimal places to display.

Value

List containing the following components:

model

final model; an object of class lm

metrics

selection metrics

others

list; info used for plotting and printing

References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

See Also

Other backward selection procedures: ols_step_backward_adj_r2(), ols_step_backward_p(), ols_step_backward_r2(), ols_step_backward_sbc(), ols_step_backward_sbic()

Examples

# stepwise backward regression
model <- lm(y ~ ., data = surgical)
ols_step_backward_aic(model)

# stepwise backward regression plot
model <- lm(y ~ ., data = surgical)
k <- ols_step_backward_aic(model)
plot(k)

# selection metrics
k$metrics
 
# final model
k$model

# include or exclude variable
# force variables to be included in the selection process
ols_step_backward_aic(model, include = c("alc_mod", "gender"))

# use index of variable instead of name
ols_step_backward_aic(model, include = c(7, 6))

# force variable to be excluded from selection process
ols_step_backward_aic(model, exclude = c("alc_heavy", "bcs"))

# use index of variable instead of name
ols_step_backward_aic(model, exclude = c(8, 1))