dual {trafo} | R Documentation |
Dual transformation for linear models
Description
The function transforms the dependent variable of a linear model using the Dual transformation. The transformation parameter can either be estimated using different estimation methods or given.
Usage
dual(object, lambda = "estim", method = "ml", lambdarange = c(0, 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.
The Dual transformation is not defined for negative values of
lambda. Defaults to |
plotit |
logical. If |
Value
An object of class trafo
. Methods such as
as.data.frame.trafo
and print.trafo
can
be used for this class.
References
Yang Z (2006). A modified family of power transformations. Economics Letters, 92(1), 14-19.
Examples
# Load data
data("cars", package = "datasets")
# Fit linear model
lm_cars <- lm(dist ~ speed, data = cars)
# Transform dependent variable using divergence minimization following
# Cramer-von-Mises
dual(object = lm_cars, method = "div.cvm", plotit = TRUE)