olsrr (version 0.6.0)

ols_step_both_sbc: Stepwise SBC regression

Description

Build regression model from a set of candidate predictor variables by entering and removing predictors based on schwarz bayesian criterion, in a stepwise manner until there is no variable left to enter or remove any more.

Usage

ols_step_both_sbc(model, ...)
# S3 method for default
ols_step_both_sbc(
  model,
  include = NULL,
  exclude = NULL,
  progress = FALSE,
  details = FALSE,
  ...
)
# S3 method for ols_step_both_sbc
plot(x, print_plot = TRUE, details = TRUE, digits = 3, ...)

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

Arguments

model

An object of class lm.

...

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, details of variable selection will be printed on screen.

x

An object of class ols_step_both_*.

print_plot

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

digits

Number of decimal places to display.

References

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

See Also

Other both direction selection procedures: ols_step_both_adj_r2(), ols_step_both_aic(), ols_step_both_r2(), ols_step_both_sbic()

Examples

if (FALSE) {
# stepwise regression
model <- lm(y ~ ., data = stepdata)
ols_step_both_sbc(model)

# stepwise regression plot
model <- lm(y ~ ., data = stepdata)
k <- ols_step_both_sbc(model)
plot(k)

# selection metrics
k$metrics

# final model
k$model

# include or exclude variables
# force variable to be included in selection process
model <- lm(y ~ ., data = stepdata)

ols_step_both_sbc(model, include = c("x6"))

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

# force variable to be excluded from selection process
ols_step_both_sbc(model, exclude = c("x2"))

# use index of variable instead of name
ols_step_both_sbc(model, exclude = c(2))

# include & exclude variables in the selection process
ols_step_both_sbc(model, include = c("x6"), exclude = c("x2"))

# use index of variable instead of name
ols_step_both_sbc(model, include = c(6), exclude = c(2))
}