car (version 2.0-20)

invResPlot: Inverse Response Plots to Transform the Response

Description

For a lm model, draws an inverse.response plot with the response $Y$ on the vertical axis and the fitted values $\hat{Y}$ on the horizontal axis. Uses nls to estimate $\lambda$ in the function $\hat{Y}=b_0+b_1Y^{\lambda}$. Adds the fitted curve to the plot. invResPlot is an alias for inverseResponsePlot.

Usage

inverseResponsePlot(model, lambda=c(-1,0,1), robust=FALSE, xlab=NULL, ...)

## S3 method for class 'lm':
inverseResponsePlot(model, lambda=c(-1,0,1), robust=FALSE, 
   xlab=NULL, labels=names(residuals(model)), ...)

invResPlot(model, ...)

Arguments

model

A lm regression object

lambda

A vector of values for lambda. A plot will be produced with curves corresponding to these lambdas and to the least squares estimate of lambda

xlab

The horizontal axis label. If NULL, it is constructed by the function.

labels

Case labels if labeling is turned on; see invTranPlot and showLabels for arguments.

robust

If TRUE, then estimation uses Huber M-estimates with the median absolute deviation to estimate scale and k= 1.345. The default is FALSE.

...

Other arguments passed to invTranPlot and then to plot.

Value

• As a side effect, a plot is produced with the response on the horizontal axis and fitted values on the vertical axis. Several lines are added to be plot as the ols estimates of the regression of $\hat{Y}$ on $Y^{\lambda}$, interpreting $\lambda$ = 0 to be natural logarithms. Numeric output is a list with elements
• lambda
  Estimate of transformation parameter for the response
• RSS
  The residual sum of squares at the minimum if robust=FALSE. If robust = TRUE, the value of Huber objective function is returned.

References

Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage. Pendergast, L, and Sheather, S. (in press). On sensitivity of response plot estimation of a robust estimation approach. Scandinavian Journal of Statistics. Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley, Chapter 7.

See Also

invTranPlot, powerTransform, showLabels

Examples

m2 <- lm(rate ~ log(len) + log(ADT) + slim + shld + log(sigs1), Highway1)
invResPlot(m2)