Estimation of Mittag-Leffler Parameters

TL;DR

This paper introduces a new, simple, and practical method for estimating parameters of Mittag-Leffler and generalized Mittag-Leffler distributions, demonstrating improved performance over existing fractional moment estimators.

Contribution

It presents a less restrictive, computationally simple estimation procedure for ML and GML distributions, enhancing their practical applicability.

Findings

The proposed estimator performs favorably compared to fractional moment estimators.

The method is less restrictive and computationally simpler.

It facilitates practical use of Mittag-Leffler models.

Abstract

We propose a procedure for estimating the parameters of the Mittag-Leffler (ML) and the generalized Mittag-Leffler (GML) distributions. The algorithm is less restrictive, computationally simple, and necessary to make these models usable in practice. A comparison with the fractional moment estimator indicated favorable results for the proposed method.