Sigma_fun {degross} | R Documentation |
Variance-covariance of sample central moments (root-n approximation) given the vector mu with the theoretical moments of order 1 to 8. CAREFUL: the result must be divided by n (= sample size)!
Description
Variance-covariance of sample central moments (root-n approximation) given the vector mu with the theoretical moments of order 1 to 8. CAREFUL: the result must be divided by n (= sample size)!
Usage
Sigma_fun(mu)
Arguments
mu |
Vector of length 8 with the first 8 theoretical central moments. |
Value
Variance-covariance matrix of the first four sample central moments (CAREFUL: a division by the sample size is further required !)
Author(s)
Philippe Lambert p.lambert@uliege.be
References
Lambert, P. (2021) Moment-based density and risk estimation from grouped summary statistics. arXiv:2107.03883.
Examples
mu = numeric(8)
dfun = function(x) dgamma(x,10,5)
mu[1] = integrate(function(x) x*dfun(x),0,Inf)$val
for (j in 2:8) mu[j] = integrate(function(x) (x-mu[1])^j*dfun(x),0,Inf)$val
Sigma_fun(mu)
[Package degross version 0.9.0 Index]