car: invTranPlot – R documentation

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invTranPlot

Choose a Predictor Transformation Visually or Numerically

Description

invTranPlot draws a two-dimensional scatterplot of Y versus X, along with the OLS fit from the regression of Y on (X?^(lam)-1)/lam. invTranEstimate finds the nonlinear least squares estimate of lambda and its standard error.

Usage

invTranPlot(x, ...)

## S3 method for class 'formula'
invTranPlot(x, data, subset, na.action, id=FALSE, ...)

## Default S3 method:
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)

Arguments

`x`	The predictor variable, or a formula with a single response and a single predictor
`y`	The response variable
`data`	An optional data frame to get the data for the formula
`subset`	Optional, as in `lm`, select a subset of the cases
`na.action`	Optional, as in `lm`, the action for missing data
`lambda`	The powers used in the plot. The optimal power than minimizes the residual sum of squares is always added unless optimal is `FALSE`.
`robust`	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`.
`family`	The transformation family to use, `"bcPower"`, `"yjPower"`, or a user-defined family.
`confidence`	returns a profile likelihood confidence interval for the optimal transformation with this confidence level. If `FALSE`, or if `robust=TRUE`, no interval is returned.
`optimal`	Include the optimal value of lambda?
`lty.lines`	line types corresponding to the powers
`lwd.lines`	the width of the plotted lines, defaults to 2 times the standard
`col`	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.
`col.lines`	color of the fitted lines corresponding to the powers. The default is to use the colors returned by `carPalette`
`key`	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.
`xlab`	Label for the horizontal axis.
`ylab`	Label for the vertical axis.
`id`	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`.
`grid`	If TRUE, the default, a light-gray background grid is put on the graph

Value

invTranPlot plots a graph and returns a data frame with lam in the first column, and the residual sum of squares from the regression for that lam 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.

Author(s)

Sanford Weisberg, sandy@umn.edu

References

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.

Examples

with(UN, invTranPlot(ppgdp, infantMortality))
with(UN, invTranEstimate(ppgdp, infantMortality))

car

Companion to Applied Regression

v3.0-10

GPL (>= 2)

Authors

John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut], Daniel Adler [ctb], Douglas Bates [ctb], Gabriel Baud-Bovy [ctb], Ben Bolker [ctb], Steve Ellison [ctb], David Firth [ctb], Michael Friendly [ctb], Gregor Gorjanc [ctb], Spencer Graves [ctb], Richard Heiberger [ctb], Pavel Krivitsky [ctb], Rafael Laboissiere [ctb], Martin Maechler [ctb], Georges Monette [ctb], Duncan Murdoch [ctb], Henric Nilsson [ctb], Derek Ogle [ctb], Brian Ripley [ctb], William Venables [ctb], Steve Walker [ctb], David Winsemius [ctb], Achim Zeileis [ctb], R-Core [ctb]

Initial release

2020-09-23