Boxplots for transformations to symmetry

symbox first transforms x to each of a series of selected powers, with each transformation standardized to mean 0 and standard deviation 1. The results are then displayed side-by-side in boxplots, permiting a visual assessment of which power makes the distribution reasonably symmetric. For the "lm" method, the response variable in the model is successively transformed.

Usage

symbox(x, ...)
# S3 method for class 'formula'
symbox(formula, data=NULL, subset, na.action=NULL, ylab,  ...)
# Default S3 method
symbox(x, powers = c(-1, -0.5, 0, 0.5, 1), start, 
  trans=bcPower, xlab="Powers", ylab, ...)
# S3 method for class 'lm'
symbox(x, powers = c(-1, -0.5, 0, 0.5, 1), start, trans=bcPower, 
                      xlab, ylab="Studentized residuals", ...)

Arguments

x: a numeric vector.
formula: a one-sided formula specifying a single numeric variable.
data, subset, na.action: as for statistical modeling functions (see, e.g., lm).
xlab, ylab: axis labels; if ylab is missing, a label will be supplied. For the "lm" method, if xlab is missing, a label will also be supplied.
powers: a vector of selected powers to which x is to be raised. For meaningful comparison of powers, 1 should be included in the vector of powers.
start: a constant to be added to x. If start is missing and trans is bcPower (the default) or bcnPower, then a start will be automatically generated if there are zero or negative values in x, and a warning will be printed; the auto-generated start is the absolute value of the minimum x plus 1 percent of the range of x.
trans: a transformation function whose first argument is a numeric vector and whose second argument is a transformation parameter, given by the powers argument; the default is bcPower, and another possibility is yjPower. bcnPower may also be used, in which case the gamma parameter is set to the value of start.
...: arguments to be passed down.

Value

as returned by boxplot.

Author

Gregor Gorjanc, John Fox jfox@mcmaster.ca.

References

Fox, J. and Weisberg, S. (2019) An R Companion to Applied Regression, Third Edition. Sage.

Examples

symbox(~ income, data=Prestige)

symbox(lm(wages ~ education + poly(age, 2) + sex, data=SLID))