Description Usage Arguments Value Author(s) References See Also Examples

View source: R/influencePlot.R

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.

1 2 3 4 5 6 7 8 | ```
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, ...)
``` |

`model` |
a linear, generalized-linear, or linear mixed model; the |

`scale` |
a factor to adjust the size of the circles. |

`xlab, ylab` |
axis labels. |

`id` |
settings for labelling points; see |

`...` |
arguments to pass to the |

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.

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

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.

`cooks.distance`

, `rstudent`

,
`hatvalues`

, `showLabels`

1 2 3 4 5 6 | ```
influencePlot(lm(prestige ~ income + education, data=Duncan))
## Not run:
influencePlot(lm(prestige ~ income + education, data=Duncan),
id=list(method="identify"))
## End(Not run)
``` |

```
Loading required package: carData
StudRes Hat CookD
minister 3.1345186 0.17305816 0.56637974
reporter -2.3970224 0.05439356 0.09898456
conductor -1.7040324 0.19454165 0.22364122
RR.engineer 0.8089221 0.26908963 0.08096807
```

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