car (version 2.0-7)

residualPlots: Residual Plots and Curvature Tests for Linear Model Fits

Description

Plots the residuals versus each term in a mean function and versus fitted values. Also computes a curvature test for each of the plots by adding a quadratic term and testing the quadratic to be zero. This is Tukey's test for nonadditivity when plotting against fitted values.

Usage

### This is a generic function with only one required argument:

residualPlots (model, ...)

## S3 method for class 'default':
residualPlots(model, terms = ~., layout = NULL, ask, 
                 main = "", fitted = TRUE, AsIs=FALSE, plot = TRUE, 
                 tests = TRUE, ...)

## S3 method for class 'lm':
residualPlots(model, ...)

## S3 method for class 'glm':
residualPlots(model, ...) 

### residualPlots calls residualPlot, so these arguments can be
### used with either function

residualPlot(model, ...)  

## S3 method for class 'default':
residualPlot(model, variable = "fitted", type = "pearson", 
                 plot = TRUE,     
                 quadratic = TRUE, 
                 smooth = FALSE, span = 1/2, smooth.lwd=lwd, smooth.lty=lty,
                 smooth.col=col.lines, 
                 labels,
                 id.method = "xy",
                 id.n = if(id.method[1]=="identify") Inf else 0,
                 id.cex=1, id.col=palette()[1],
                 col = palette()[1], col.lines = palette()[2], 
                 xlab, ylab, lwd = 1, lty=1, grid=TRUE, ...)   
                 
## S3 method for class 'lm':
residualPlot(model, ...) 
  
## S3 method for class 'glm':
residualPlot(model, variable = "fitted", type = "pearson", 
                 plot = TRUE, quadratic = FALSE, smooth = TRUE, ...)

Arguments

model
A regression object.
terms
A one-sided formula that specifies a subset of the predictors. One residual plot is drawn for each specified. The default ~. is to plot against all predictors. For example, the specification terms = ~.-X3 would plot against
layout
If set to a value like 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 la
ask
If TRUE, ask the user before drawing the next plot; if FALSE, don't ask.
main
Main title for the graphs. The default is main="" for no title.
fitted
If TRUE, the default, include the plot against fitted values.
AsIs
If FALSE, the default, terms that use the as-is function I are skipped; if TRUE, they are included.
plot
If TRUE, draw the plot(s).
tests
If TRUE, display the curvature tests.
...
Additional arguments passed to residualPlot and then to plot.
variable
Quoted variable name for the horizontal axis, or "fitted" to plot versus fitted values.
type
Type of residuals to be used. Pearson residuals are appropriate for lm objects since these are equivalent to ordinary residuals with ols and correctly weighted residuals with wls. Any quoted string that is an appropriate value of the
quadratic
if TRUE, fits the quadratic regression of the vertical axis on the horizontal axis and displays a lack of fit test. Default is TRUE for lm and FALSE for glm.
smooth
if TRUE fits a loess smooth using the settings given below. Defaults to FALSE for lm objects and TRUE for glm objects.
span, smooth.lwd, smooth.lty, smooth.col
Should a lowess smooth be added to the figure? The span is the smoothing parameter for lowess, smooth.lwd, smooth.lty, and smooth.col are, respectively, the width, type, and color of the line drawn o
id.method,labels,id.n,id.cex,id.col
Arguments for the labelling of points. The default is id.n=0 for labeling no points. See showLabels for details of these arguments.
col
default color for points
col.lines
default color for lines
xlab
X-axis label. If not specified, a useful label is constructed by the function.
ylab
Y-axis label. If not specified, a useful label is constructed by the function.
lwd
line width for lines.
lty
line type for quadratic.
grid
If TRUE, the default, a light-gray background grid is put on the graph

Value

  • For lm objects, returns a data.frame with one row for each plot drawn, one column for the curvature test statistic, and a second column for the corresponding p-value. This function is used primarily for its side effect of drawing residual plots.

Details

residualPlots draws one or more residuals plots depending on the value of the terms and fitted arguments. If terms = ~ ., the default, then a plot is produced of residuals versus each first-order term in the formula used to create the model. Interaction terms, spline terms, and polynomial terms of more than one predictor are skipped. In addition terms that use the as-is function, e.g., I(X^2), will also be skipped unless you set the argument AsIs=TRUE. A plot of residuals versus fitted values is also included unless fitted=FALSE. In addition to plots, a table of curvature tests is displayed. For plots against a term in the model formula, say X1, the test displayed is the t-test for for I(X^2) in the fit of update, model, ~. + I(X^2)). Econometricians call this a specification test. For factors, the displayed plot is a boxplot, and no curvature test is computed. For fitted values, the test is Tukey's one-degree-of-freedom test for nonadditivity. You can suppress the tests with the argument tests=FALSE. residualPlot, which is called by residualPlots, should be viewed as an internal function, and is included here to display its arguments, which can be used with residualPlots as well. The residualPlot function returns the curvature test as an invisible result. residCurvTest computes the curvature test only. For any factors a boxplot will be drawn. For any polynomials, plots are against the linear term. Other non-standard predictors like B-splines are skipped.

References

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition. Sage. Weisberg, S. (2005) Applied Linear Regression, Third Edition, Wiley, Chapter 8

See Also

See Also lm, identify, showLabels

Examples

Run this code
residualPlots(lm(longley))

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