Plot Leverage vs. Fitted Values to Visualize Inflential Observations

Creates a plot of leverage values versus the linear fitted values, including an identification of points with a large Cook's distance, to visualize high-leverage and influential observations.

Usage

lm_plot.infl(
  mdl,
  ...,
  parms = lm_plot.parms(mdl),
  df = lm_plot.df(mdl, parms = parms)
)

Arguments

mdl

A fitted model object (typically from lm).

...

Additional arguments (not currently used).

parms

List of plotting parameters, usually from lm_plot.parms().

df

Data frame with augmented model data. Defaults to lm_plot.df(mdl).

Value

A ggplot object representing the comb plot of residuals vs sequence, indicating influential points. Included as an attribute "parms" is a list containing:

• lim Plotted limits on x and y axes.

Details

The plot visualizes the calculated leverage of individual data points, defined as the diagonal element of the 'hat' matrix, as a function of the fitted values and implicitly relative to their location in the field of predictor variables, and the threshold value of high leverage is indicated. In addition, Cook's distance can be used to label influential points, along with outlier and regular points.

See also

lm_plot.df, lm_plot.parms, outlier

Examples

mdl <- lm(Sepal.Length ~ Sepal.Width, data = iris)
result <- lm_plot.infl(mdl)