# influencPlot

From car v1.2-16
by John Fox

##### Regression Influence Plot

This function creates a "bubble" plot of studentized residuals by hat values, with the areas of the circles representing the observations proportional to Cook's distances. 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.

- Keywords
- regression

##### Usage

```
influencePlot(model, ...)
## S3 method for class 'lm':
influencePlot(model, scale=10, col=c(1,2), identify=c(TRUE, FALSE, "auto"),
labels=names(rstud), cex.identify=par("cex"), col.identify=par("col"), ...)
```

##### Arguments

- model
- a linear or generalized-linear model.
- scale
- a factor to adjust the size of the circles.
- col
- colors for plotting points that do not and do have noteworthy Cook's distances.
- identify
- identify points; if
`TRUE`

, the default, identify points interactively; if`"auto"`

then points with large Cook's distances will automatically be identified. - labels
- a vector of observation labels.
- cex.identify, col.identify
- for point labels.
- ...
- arguments to pass to the
`plot`

function.

##### Value

- Returns the indices of identified points.

##### Note

This function used to be named `influence.plot`

; the name was changed to avoid confusion with
the `influence`

generic function.

##### References

J. Fox (2002)
*An R and S-PLUS Companion to Applied Regression*. Sage.

##### See Also

##### Examples

```
influencePlot(lm(prestige ~ income + education, data=Duncan),
identify="auto")
```

*Documentation reproduced from package car, version 1.2-16, License: GPL (>= 2)*

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