estim_lme {trafo} | R Documentation |
Wrapper function for estimation methods - linear mixed models
Description
Wrapper function for estimation methods - linear mixed models
Usage
estim_lme(lambda, y, formula, data, rand_eff, method, trafo, custom_func,
custom_func_std)
Arguments
lambda |
transformation parameter |
y |
vector of response variables |
formula |
a formula object that contains the dependent and the explanatory measures |
data |
the data.frame that is given to function nlme and that contains the regression variables. |
rand_eff |
the random effect extracted from the lme object. |
method |
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. |
trafo |
a character string that selects the transformation. |
custom_func |
a function that determines a customized transformation. |
custom_func_std |
a function that determines a customized standard transformation. |
Value
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.