# infIndexPlot

##### Influence Index Plot

Provides index plots of Cook's distances, leverages, Studentized residuals, and outlier significance levels for a regression object.

- Keywords
- regression, hplot

##### Usage

`infIndexPlot(model, ...)`influenceIndexPlot(model, ...)

# S3 method for lm
infIndexPlot(model,
vars=c("Cook", "Studentized", "Bonf", "hat"),
main="Diagnostic Plots",
labels, id.method = "y",
id.n = if(id.method[1]=="identify") Inf else 0,
id.cex=1, id.col=palette()[1], id.location="lr", grid=TRUE, ...)

##### Arguments

- model
A regression object of class

`lm`

or`glm`

.- vars
All the quantities listed in this argument are plotted. Use

`"Cook"`

for Cook's distances,`"Studentized"`

for Studentized residuals,`"Bonf"`

for Bonferroni p-values for an outlier test, and and`"hat"`

for hat-values (or leverages). Capitalization is optional. All may be abbreviated by the first one or more letters.- main
main title for graph

- id.method,labels,id.n,id.cex,id.col,id.location
Arguments for the labelling of points. The default is

`id.n=0`

for labeling no points. See`showLabels`

for details of these arguments.- grid
If TRUE, the default, a light-gray background grid is put on the graph

- …
Arguments passed to

`plot`

##### Value

Used for its side effect of producing a graph. Produces four index plots of Cook's distance, Studentized Residuals, the corresponding Bonferroni p-values for outlier tests, and leverages.

##### References

Cook, R. D. and Weisberg, S. (1999)
*Applied Regression, Including Computing and Graphics.* Wiley.

Fox, J. (2008)
*Applied Regression Analysis and Generalized Linear Models*,
Second Edition. Sage.

Fox, J. and Weisberg, S. (2011)
*An R Companion to Applied Regression*, Second Edition, Sage.

Weisberg, S. (2014)
*Applied Linear Regression*, Fourth Edition, Wiley.

##### See Also

##### Examples

```
# NOT RUN {
m1 <- lm(prestige ~ income + education + type, Duncan)
influenceIndexPlot(m1)
# }
```

*Documentation reproduced from package car, version 2.1-6, License: GPL (>= 2)*