arXiv Open Access 2025

Robust estimation with latin hypercube sampling: a central limit theorem for Z-estimators

Faouzi Hakimi

Lihat Sumber

Abstrak

Latin hypercube sampling (LHS) is a widely used stratified sampling method in computer experiments. In this work, we extend the existing convergence results for the sample mean under LHS to the broader class of $Z$-estimators, estimators defined as the zeros of a sample mean function. We derive the asymptotic variance of these estimators and demonstrate that it is smaller when using LHS compared to traditional independent and identically distributed (i.i.d.) sampling. Furthermore, we establish a Central Limit Theorem for $Z$-estimators under LHS, providing a theoretical foundation for its improved efficiency.

Topik & Kata Kunci

math.ST

Penulis (1)

Faouzi Hakimi

Format Sitasi

APA MLA BibTeX

Hakimi, F. (2025). Robust estimation with latin hypercube sampling: a central limit theorem for Z-estimators. https://arxiv.org/abs/2502.06321

Akses Cepat

Lihat di Sumber

Informasi Jurnal

Tahun Terbit: 2025
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓