Estimation, Comparison and Selection of Transformations
Data frame with transformed variables
First check of assumptions to find suitable transformations
Bickel-Doksum transformation for linear models
Box-Cox transformation for linear models
Box-Cox shift transformation for linear models
Diagnostics for fitted models
Diagnostics for two differently transformed models
Diagnostics for an untransformed and a transformed model
Internal diagnostic functions
Divergence minimization by Cramer von Mises
Divergence minimization by Kullback-Leibler
Divergence minimization by Kolmogorov Smirnov
Dual transformation for linear models
Estimation of optimal transformation parameter - lm
Box Cox Estimation - lme
Wrapper function for estimation methods - linear models
Wrapper function for estimation methods - linear mixed models
Function that fits model with transformed dependent variable
Function that bundles the return of a trafo object
Glog transformation for linear models
Gpower transformation for linear models
Kurtosis
Log shift transformation for linear models
Log shift opt transformation for linear models
Log transformation for linear models
Manly transformation for linear models
Maximum Likelihood
Modulus transformation for linear models
Neg log transformation for linear models
One parameter transformations for linear models
One parameter transformations
Plots for linear models with transformed dependent variable
Plot for regression models with untransformed and transformed dependen...
Plot for optimal transformation parameter - linear models
Prints diagnostics of two trafo objects
Prints diagnostics of an untransformed and a transformed model
Prints summary of trafo_compare objects
Print summary trafo
Prints object of type trafo
Prints object of type trafo_compare
Prints object of type trafo_lm
Reciprocal transformation for linear models
Skewness minimization by Molina
Square-root shift transformation for linear models
Summary for two differently transformed models
Summary for linear models with untransformed and transformed dependent...
An R package supporting the selection of a suitable transformation
Compares linear models with transformed dependent variable
Fits transformed linear models
Transformations without parameter for linear models
Transformations without transformation parameter
Yeo-Johnson transformation for linear models
Estimation, selection and comparison of several families of transformations. The families of transformations included in the package are the following: Bickel-Doksum (Bickel and Doksum 1981 <doi:10.2307/2287831>), Box-Cox, Dual (Yang 2006 <doi:10.1016/j.econlet.2006.01.011>), Glog (Durbin et al. 2002 <doi:10.1093/bioinformatics/18.suppl_1.S105>), gpower (Kelmansky et al. 2013 <doi:10.1515/sagmb-2012-0030>), Log, Log-shift opt (Feng et al. 2016 <doi:10.1002/sta4.104>), Manly, modulus (John and Draper 1980 <doi:10.2307/2986305>), Neglog (Whittaker et al. 2005 <doi:10.1111/j.1467-9876.2005.00520.x>), Reciprocal and Yeo-Johnson. The package simplifies to compare linear models with untransformed and transformed dependent variable as well as linear models where the dependent variable is transformed with different transformations. Furthermore, the package employs maximum likelihood approaches, moments optimization and divergence minimization to estimate the optimal transformation parameter.