Cooks' D bar plot
Bar Plot of cook's distance to detect observations that strongly influence fitted values of the model.
ols_plot_cooksd_bar(model, print_plot = TRUE)
model |
An object of class |
print_plot |
logical; if |
Cook's distance was introduced by American statistician R Dennis Cook in 1977. It is used to identify influential data points. It depends on both the residual and leverage i.e it takes it account both the x value and y value of the observation.
Steps to compute Cook's distance:
Delete observations one at a time.
Refit the regression model on remaining n - 1 observations
examine how much all of the fitted values change when the ith observation is deleted.
A data point having a large cook's d indicates that the data point strongly influences the fitted values.
ols_plot_cooksd_bar returns a list containing the
following components:
outliers |
a |
threshold |
|
ols_cooksd_barplot() has been deprecated. Instead use ols_plot_cooksd_bar().
[ols_plot_cooksd_chart()]
model <- lm(mpg ~ disp + hp + wt, data = mtcars) ols_plot_cooksd_bar(model)
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