estim_lm function

Wrapper function for estimation methods - linear models

estim_lm(lambda, y, x, method, trafo, custom_func, custom_func_std)

Arguments

• lambda: transformation parameter
• y: vector of response variables
• x: matrix of regressors
• 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". 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.

Returns

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.