boxcoxshift function

Box-Cox shift transformation for linear models

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.

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

Arguments

• 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.

Returns

an object of class trafo.

References

Box GEP, Cox DR (1964). An Analysis of Transformations. Journal of the Royal Statistical Society B, 26(2), 211-252.