car: influencePlot – R documentation

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influencePlot

Regression Influence Plot

Description

This function creates a “bubble” plot of Studentized residuals versus hat values, with the areas of the circles representing the observations proportional to the value Cook's distance. Vertical reference lines are drawn at twice and three times the average hat value, horizontal reference lines at -2, 0, and 2 on the Studentized-residual scale.

Usage

influencePlot(model, ...)

## S3 method for class 'lm'
influencePlot(model, scale=10,  
 xlab="Hat-Values", ylab="Studentized Residuals", id=TRUE, ...)

## S3 method for class 'lmerMod'
influencePlot(model, ...)

Arguments

`model`	a linear, generalized-linear, or linear mixed model; the `"lmerMod"` method calls the `"lm"` method and can take the same arguments.
`scale`	a factor to adjust the size of the circles.
`xlab, ylab`	axis labels.
`id`	settings for labelling points; see `link{showLabels}` for details. To omit point labelling, set `id=FALSE`; the default, `id=TRUE` is equivalent to `id=list(method="noteworthy", n=2, cex=1, col=carPalette()[1], location="lr")`. The default `method="noteworthy"` is used only in this function and indicates setting labels for points with large Studentized residuals, hat-values or Cook's distances. Set `id=list(method="identify")` for interactive point identification.
`...`	arguments to pass to the `plot` and `points` functions.

Value

If points are identified, returns a data frame with the hat values, Studentized residuals and Cook's distance of the identified points. If no points are identified, nothing is returned. This function is primarily used for its side-effect of drawing a plot.

Author(s)

John Fox jfox@mcmaster.ca, minor changes by S. Weisberg sandy@umn.edu

References

Fox, J. (2016) Applied Regression Analysis and Generalized Linear Models, Third Edition. Sage.

Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition, Sage.

Examples

influencePlot(lm(prestige ~ income + education, data=Duncan))
## Not run: 
influencePlot(lm(prestige ~ income + education, data=Duncan), 
    id=list(method="identify"))

## End(Not run)

car

Companion to Applied Regression

v3.0-10

GPL (>= 2)

Authors

John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut], Daniel Adler [ctb], Douglas Bates [ctb], Gabriel Baud-Bovy [ctb], Ben Bolker [ctb], Steve Ellison [ctb], David Firth [ctb], Michael Friendly [ctb], Gregor Gorjanc [ctb], Spencer Graves [ctb], Richard Heiberger [ctb], Pavel Krivitsky [ctb], Rafael Laboissiere [ctb], Martin Maechler [ctb], Georges Monette [ctb], Duncan Murdoch [ctb], Henric Nilsson [ctb], Derek Ogle [ctb], Brian Ripley [ctb], William Venables [ctb], Steve Walker [ctb], David Winsemius [ctb], Achim Zeileis [ctb], R-Core [ctb]

Initial release

2020-09-23