leveragePlots(model, terms = ~., layout = NULL, ask, 
    main, ...)
leveragePlot(model, ...)
## S3 method for class 'lm':
leveragePlot(model, term.name,
    id.method = list(abs(residuals(model, type="pearson")), "x"),
    labels, 
    id.n = if(id.method[1]=="identify") Inf else 0,
    id.cex=1, id.col=palette()[1], 
    col=palette()[1], col.lines=palette()[2], lwd=2, 
    xlab, ylab, main="Leverage Plot", grid=TRUE, ...)
## S3 method for class 'glm':
leveragePlot(model, ...)lm~. is to plot against all numeric predictors.  For example, the
specification terms = ~ . - X3 would c(1, 1) or c(4, 3), the layout
of the graph will have this many rows and columns.  If not set, the program
will select an appropriate layout.  If the number of graphs exceed nine, you 
must select the laTRUE, a menu is provided in the R Console for the
user to select the term(s) to plot.leveragePlots.id.n=0 for labeling no points.  See
    showLabels for details of these arguments.2 (see par).NULL. These functions are used for their side effect: producing
  plots.leveragePlots. 
  
  The model can contain factors and interactions. A leverage plot can be
  drawn for each term in the model, including the constant.
  
  leveragePlot.glm is a dummy function, which generates an error message.avPlotsleveragePlots(lm(prestige~(income+education)*type, data=Duncan))Run the code above in your browser using DataLab