estim_lm

lambda

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". In case of no and
log transformation "NA" can be selected since no optimization is necessary
for these two transformation types.

method

a character string that selects the transformation.

trafo

a function that determines a customized transformation.

custom_func

a function that determines a customized standard
transformation.

custom_func_std

Wrapper function for estimation methods - linear models

internal

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.

estim_lm: Wrapper function for estimation methods - linear models

Description

Usage

Arguments

Value