IGMM.default {LambertW} | R Documentation |
Computes via iterations this value of theta that generates input data x, as close as possible to the theoretical X. Implementation of the Algorithm described in Goerg (2009).
## Default S3 method: IGMM(y, robust = FALSE, tol = 10^(-6), gamma_x = 0)
y |
data |
robust |
Should the skewness be measured in a robust way (see mc )? default FALSE |
tol |
tolerance level for stopping of iterations (conversion reached) |
gamma_x |
Theoretical skewness of input X; by default 0 |
theta |
optimal theta |
iterations |
number of iterations |
call |
function call |
Georg M. Goerg
Goerg, G.M. (2009). “Lambert W Random Variables - A new class of skewed distribution functions”. Unpublished
x=rnorm(1000) fit=IGMM(x) summary(fit) y=rLambertW(n=1000, c(0.1, 2,1)) fity=IGMM(y) summary(fity) plot(fity)