est_lm: Estimation of optimal transformation parameter - lm

In akreutzmann/trafo: Estimation, Comparison and Selection of Transformations

Description

Estimation of optimal transformation parameter - lm

Usage

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)

Value

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

akreutzmann/trafo documentation built on Sept. 14, 2020, 9:03 p.m.