invTranPlot
draws a two-dimensional scatterplot of \(Y\) versus
\(X\), along with the OLS
fit from the regression of \(Y\) on
\((X^{\lambda}-1)/\lambda\). invTranEstimate
finds the nonlinear least squares estimate of \(\lambda\) and its
standard error.
invTranPlot(x, ...)# S3 method for formula
invTranPlot(x, data, subset, na.action, id=FALSE, ...)
# S3 method for default
invTranPlot(x, y, lambda=c(-1, 0, 1), robust=FALSE,
lty.lines=rep(c("solid", "dashed", "dotdash", "longdash", "twodash"),
length=1 + length(lambda)), lwd.lines=2,
col=carPalette()[1], col.lines=carPalette(),
xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
family="bcPower", optimal=TRUE, key="auto", id=FALSE,
grid=TRUE, ...)
invTranEstimate(x, y, family="bcPower", confidence=0.95, robust=FALSE)
The predictor variable, or a formula with a single response and a single predictor
The response variable
An optional data frame to get the data for the formula
Optional, as in lm
, select a subset of the cases
Optional, as in lm
, the action for missing data
The powers used in the plot. The optimal power than minimizes
the residual sum of squares is always added unless optimal is FALSE
.
If TRUE
, then the estimated transformation is computed using
Huber M-estimation with the MAD used to estimate scale and k=1.345. The
default is FALSE
.
The transformation family to use, "bcPower"
,
"yjPower"
, or a user-defined family.
returns a profile likelihood confidence interval for the optimal
transformation with this confidence level. If FALSE
, or if robust=TRUE
,
no interval is returned.
Include the optimal value of lambda?
line types corresponding to the powers
the width of the plotted lines, defaults to 2 times the standard
color(s) of the points in the plot. If you wish to distinguish points
according to the levels of a factor, we recommend using symbols, specified with
the pch
argument, rather than colors.
color of the fitted lines corresponding to the powers. The
default is to use the colors returned by carPalette
The default is "auto"
, in which case a legend is added to
the plot, either above the top marign or in the bottom right or top right corner.
Set to NULL to suppress the legend.
Label for the horizontal axis.
Label for the vertical axis.
controls point identification; if FALSE
(the default), no points are identified;
can be a list of named arguments to the showLabels
function;
TRUE
is equivalent to list(method=list(method="x", n=2, cex=1, col=carPalette()[1], location="lr")
,
which identifies the 2 points with the most extreme horizontal values --- i.e., the response variable in the model.
Additional arguments passed to the plot method, such as pch
.
If TRUE, the default, a light-gray background grid is put on the graph
invTranPlot
plots a graph and returns a data frame with \(\lambda\) in the
first column, and the residual sum of squares from the regression
for that \(\lambda\) in the second column.
invTranEstimate
returns a list with elements lambda
for the
estimate, se
for its standard error, and RSS
, the minimum
value of the residual sum of squares.
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.
# NOT RUN {
with(UN, invTranPlot(ppgdp, infantMortality))
with(UN, invTranEstimate(ppgdp, infantMortality))
# }
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