IGMM.default {LambertW}R Documentation

Iterative Generalized Method of Moments (IGMM)

Description

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).

Usage

## Default S3 method:
IGMM(y, robust = FALSE, tol = 10^(-6), gamma_x = 0)

Arguments

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

Value

theta optimal theta
iterations number of iterations
call function call

Author(s)

Georg M. Goerg

References

Goerg, G.M. (2009). “Lambert W Random Variables - A new class of skewed distribution functions”. Unpublished

Examples

x=rnorm(1000)
fit=IGMM(x)
summary(fit)

y=rLambertW(n=1000, c(0.1, 2,1))
fity=IGMM(y)
summary(fity)
plot(fity)


[Package LambertW version 0.1.6 Index]