trafo_lm: Fits transformed linear models
In akreutzmann/trafo: Estimation, Comparison and Selection of Transformations

Description Usage Arguments Value See Also Examples

Function trafo_lm fits linear models with transformed dependent variable. The main return are two lm objects where one is the untransformed linear model and the other one the transformed linear model.

1 2	trafo_lm(object, trafo = "boxcox", lambda = "estim", method = "ml", lambdarange = NULL, std = FALSE, custom_trafo = NULL)

`object`	an object of type `lm`.
`trafo`	a character string. Different transformations can be used for transforming the dependent variable in a linear model: (i) "bickeldoksum", (ii) "boxcox", (iii) "dual", (iv) "glog", (v) "gpower", (vi) "log", (vii) "logshiftopt", (viii) "manly", (ix) "modulus", (x) "neglog", (xi) "reciprocal", (xii) "yeojohnson". Defaults to "boxcox".
`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 `NULL` which means that the default value of the chosen transformation is used.
`std`	logical. If `TRUE`, the transformed model is returned based on the standardized/scaled transformation. Defaults to `FALSE`.
`custom_trafo`	a list. The list has two elements where the first element is a function specifying the desired transformation and the second element is a function specifying the corresponding standardized transformation. Defaults to `NULL`.

An object of class trafo_lm. Methods such as diagnostics.trafo_lm, print.trafo_lm, plot.trafo_lm and summary.trafo_lm can be used for this class.

bickeldoksum, boxcox, dual, glog, gpower, log, logshiftopt, manly, modulus, neglog, sqrtshift, yeojohnson

# Load data
data("cars", package = "datasets")

# Fit linear model
lm_cars <- lm(dist ~ speed, data = cars)

# Compare untransformed and transformed model
trafo_lm(object = lm_cars, trafo = "bickeldoksum", method = "skew", 
lambdarange = c(1e-11, 2))