Random weighting estimation of parameters in generalized Gaussian distribution

This paper studies random weighting estimation of shape and scale parameters in generalized Gaussian distribution (GGD). An expression is established to describe the relationship between moments and parameters. The strong convergence for random weighting estimation of GGD parameters is also rigorously proved. Computational simulations and practical experiments are presented to demonstrate the efficacy for random weighting estimation of GGD parameters.