New Sufficient Conditions for Moment-determinacy via Probability Density Tails

TL;DR

This paper introduces new, easy-to-check conditions based on the tail behavior of probability density functions that ensure a distribution is uniquely determined by its moments, extending existing results in the field.

Contribution

It proposes a general tail-based condition (D) for moment determinacy, applicable in both Stieltjes and Hamburger cases, and extends recent theoretical results.

Findings

Condition (D) effectively guarantees moment determinacy.

Theorems and corollaries established for both distribution types.

Provides an illustrative example demonstrating the condition's application.

Abstract

One of the ways to characterize a probability distribution is to show that it is moment-determinate, uniquely determined by knowing all its moments. The uniqueness, in the absolutely continuous case, depends entirely on the behaviour of the tails of the density function f. We find and exploit a condition, (D), in terms only of f which is of a `general' form and easy to check. Condition (D), showing the `speed' for f to tend to zero, is sufficient to conclude the moment determinacy. We establish a series of theorems and corollaries in both Stieltjes and Hamburger cases and provide an interesting illustrative example. The results in this paper are either new or extend some recently published results.