est_lm function

Estimation of optimal transformation parameter - lm

est_lm(y, x, method, lambdarange, trafo, custom_func, custom_func_std, ...)

Arguments

• 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".
• lambdarange: range for the estimation parameter expr(lambda) - default c(-2, 2)

Returns

modelt An object of type lm employing the transformed vector yt as the response variable