On the lower expected star discrepancy for jittered sampling than simple random sampling

TL;DR

This paper compares the expected star discrepancy between jittered sampling and simple random sampling, proving a strong partition principle for star discrepancy.

Contribution

It introduces a strong partition principle for star discrepancy and analyzes how jittered sampling reduces discrepancy compared to random sampling.

Findings

Jittered sampling has lower expected star discrepancy than random sampling.

A strong partition principle for star discrepancy is established.

Theoretical comparison of sampling methods' discrepancy properties.

Abstract

We compare expected star discrepancy under jittered sampling with simple random sampling, and the strong partition principle for the star discrepancy is proved.