Wrapper function for estimation methods - linear mixed models
estim_lme(lambda, y, formula, data, rand_eff, method, trafo, custom_func,
custom_func_std)transformation parameter
vector of response variables
a formula object that contains the dependent and the explanatory measures
the data.frame that is given to function nlme and that contains the regression variables.
the random effect extracted from the lme object.
a character string. In order to determine the optimal parameter for the transformation five different estimation methods can be chosen (i) Maximum-Likelihood ("ml"); (ii) skewness minimization ("skew"); (iii) minimization of Kolmogorov-Smirnov divergence ("div.ks"); (iv) minimization of Cramer von Mises divergence ("div.cvm"); (v) minimization of Kullback Leibler divergence ("div.kl"). In case of no and log transformation "NA" can be selected since no optimization is necessary for these two transformation types.
a character string that selects the transformation.
a function that determines a customized transformation.
a function that determines a customized standard transformation.
Depending on the selected method the return is a log
likelihood, a skewness, a pooled skewness or a Kolmogorov-Smirnov, Cramer
von Mises or Kullback Leibler divergence.