Limit theorems for quasi-arithmetic means of random variables with applications to point estimations for the Cauchy distribution

TL;DR

This paper develops limit theorems for complex-valued quasi-arithmetic means of random variables, enabling new simple, unbiased estimators for Cauchy distribution parameters.

Contribution

It introduces limit theorems for complex-valued quasi-arithmetic means, facilitating the derivation of straightforward estimators for Cauchy distribution parameters.

Findings

Derived unbiased strongly-consistent estimators for Cauchy parameters

Established limit theorems applicable to complex-valued quasi-arithmetic means

Provided closed-form solutions for parameter estimation

Abstract

We establish some limit theorems for quasi-arithmetic means of random variables. This class of means contains the arithmetic, geometric and harmonic means. Our feature is that the generators of quasi-arithmetic means are allowed to be complex-valued, which makes considerations for quasi-arithmetic means of random variables which could take negative values possible. Our motivation for the limit theorems is finding simple estimators of the parameters of the Cauchy distribution. By applying the limit theorems, we obtain some closed-form unbiased strongly-consistent estimators for the joint of the location and scale parameters of the Cauchy distribution, which are easy to compute and analyze.