invTranPlot {car} | R Documentation

## 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 (Y^(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, ...)

    ## 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=palette()[1], col.lines=palette(),
            xlab=deparse(substitute(x)), ylab=deparse(substitute(y)),
            family="bcPower", optimal=TRUE, key="auto",
            id.method = "x",
            labels,
            id.n = if(id.method[1]=="identify") Inf else 0,
            id.cex=1, id.col=palette()[1], id.location="lr", 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 `palette`
`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.method,labels,id.n,id.cex,id.col,id.location` | Arguments for the labelling of points. The default is `id.n=0` for labeling no points. See `showLabels` for details of these arguments.
`...` | 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.

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 Wiley.

### See Also

`inverseResponsePlot`,`optimize`

### Examples

    with(UN, invTranPlot(gdp, infant.mortality))
    with(UN, invTranEstimate(gdp, infant.mortality))

[Package car version 2.1-6 Index]