invResPlot {car} | R Documentation |
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
.
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, id=FALSE, ...)
invResPlot(model, ...)
model |
A |
lambda |
A vector of values for lambda. A plot will be produced with curves corresponding to these lambdas and to the nonlinear least squares estimate of lambda. |
robust |
If |
xlab |
The horizontal axis label. If |
id |
controls point identification; if |
... |
Other arguments passed to |
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. |
Sanford Weisberg, sandy@umn.edu
Fox, J. and Weisberg, S. (2011) An R Companion to Applied Regression, Second Edition, Sage.
Prendergast, L. A., & Sheather, S. J. (2013) On sensitivity of inverse response plot estimation and the benefits of a robust estimation approach. Scandinavian Journal of Statistics, 40(2), 219-237.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley, Chapter 7.
invTranPlot
, powerTransform
,
showLabels
m2 <- lm(rate ~ log(len) + log(adt) + slim + shld + log(sigs1), Highway1)
invResPlot(m2)