inv.res.plot {alr3} | R Documentation |
For a lm
object, draws an inverse.response plot with the response Y on the
vertical axis and the fitted values Yhat
on the horizontal axis. Uses nls
to
estimate lambda in the function
Yhat = b0 + b1(Y)^(lambda).
Adds the fitted curve to the plot.
inv.res.plot is an alias for inverse.response.plot.
inverse.response.plot(m, lambda=c(0,1),maxiter=100,xlab=NULL,...)
m |
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. |
maxiter |
Passed to |
... |
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 Yhat 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 |
se |
Standard error of the estimate |
RSS |
The residual sum of squares at the minimum |
Sanford Weisberg, sandy@stat.umn.edu
S. Weisberg (2005), Applied Linear Regression, third edition, Wiley, Chapter 7
inv.tran.plot
and inv.tran.estimate
, for which
this is just a convenient front-end, and nls
.
data(highway) highway$Sigs1 <- (round(highway$Sigs*highway$Len)+1)/highway$Len attach(highway) d <- data.frame(Rate=Rate,logLen=logb(Len,2), logADT=logb(ADT,2),logTrks=logb(Trks,2), Slim=Slim,Shld=Shld,logSigs1=logb(Sigs1,2)) attach(d) m2 <- lm(Rate~logLen+logADT+logTrks+Slim+Shld+logSigs1,d) inv.res.plot(m2,key=c(6,2))