delta.GMM {LambertW} | R Documentation |
Given mu_x and sigma_x, it computes the value of delta such that the sample skewness of the back transformed data equals the theoretical one of X, gamma(X). In particular, for Gaussian and student-t input gamma(X) = 0 (default value), so this finds the delta that "symmetrizes" the backtransformed data.
A robust measure of the skewness is possible via the MedCouple estimator.
delta.GMM(y, robust = FALSE, c = mean(y), s = sqrt(var(y)), gamma_x = 0, ...)
y |
data |
robust |
should the skewness be measured in a robust way? robust=TRUE/FALSE ; default is FALSE |
c |
the value that centers y |
s |
standardizing constant for y |
gamma_x |
theoretical skewness. default value gamma_x = 0 |
... |
... |
the parameter vector theta
Georg M. Goerg
Goerg, G.M. (2009). “Lambert W Random Variables - A new class of skewed distribution functions”. Unpublished