Regression Leverage Plots
These functions display a generalization, due to Sall (1990) and Cook and Weisberg (1991), of added-variable plots to multiple-df terms in a linear model. When a term has just 1 df, the leverage plot is a rescaled version of the usual added-variable (partial-regression) plot.
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=="identify") Inf else 0, id.cex=1, id.col=palette(), col=palette(), col.lines=palette(), lwd=2, xlab, ylab, main="Leverage Plot", grid=TRUE, ...) ## S3 method for class 'glm': leveragePlot(model, ...)
- model object produced by
- A one-sided formula that specifies a subset of the predictors.
One added-variable plot is drawn for each term. The default
~.is to plot against all numeric predictors. For example, the specification
terms = ~ . - X3would
- If set to a value like
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 la
TRUE, a menu is provided in the R Console for the user to select the term(s) to plot.
- xlab, ylab
- axis labels; if missing, labels will be supplied.
- title for plot; if missing, a title will be supplied.
- arguments passed down to method functions.
- Quoted name of term in the model to be plotted; this argument
is omitted for
- Arguments for the labelling of
points. The default is
id.n=0for labeling no points. See
showLabelsfor details of these arguments.
- color(s) of points
- color of the fitted line
- line width; default is
- If TRUE, the default, a light-gray background grid is put on the graph
The function intended for direct use is
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.
NULL. These functions are used for their side effect: producing plots.
Cook, R. D. and Weisberg, S. (1991). Added Variable Plots in Linear Regression. In Stahel, W. and Weisberg, S. (eds.), Directions in Robust Statistics and Diagnostics. Springer, 47-60. 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. Sall, J. (1990) Leverage plots for general linear hypotheses. American Statistician 44, 308--315.