boxcoxshift: Box-Cox shift transformation for linear models
In trafo: Estimation, Comparison and Selection of Transformations

Description Usage Arguments Value References

The function transforms the dependent variable of a linear model using the Box-Cox shift transformation. The shift is not estimated but determined to the value min(y) + 1 in order to make all y positive. The transformation parameter can either be estimated using different estimation methods or given.

1 2	boxcoxshift(object, lambda = "estim", method = "ml", lambdarange = c(-2, 2), plotit = TRUE)

`object`	an object of type lm.
`lambda`	either a character named "estim" if the optimal transformation parameter should be estimated or a numeric value determining a given value for the transformation parameter. Defaults to "estim".
`method`	a character string. Different estimation methods can be used for the estimation of the optimal transformation parameter: (i) Maximum likelihood approach ("ml"), (ii) Skewness minimization ("skew"), (iii) Kurtosis optimization ("kurt"), (iv) Divergence minimization by Kolmogorov-Smirnov ("div.ks"), by Cramer-von-Mises ("div.cvm") or by Kullback-Leibler ("div.kl"). Defaults to "ml".
`lambdarange`	a numeric vector with two elements defining an interval that is used for the estimation of the optimal transformation parameter. Defaults to `c(-2, 2)`.
`plotit`	logical. If `TRUE`, a plot that illustrates the optimal transformation parameter or the given transformation parameter is returned. Defaults to `TRUE`.