Saved in:
Bibliographic Details
Main Authors: Morimoto, Toshinari, Hung, Hung, Huang, Su-Yun
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2407.19959
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866914891499044864
author Morimoto, Toshinari
Hung, Hung
Huang, Su-Yun
author_facet Morimoto, Toshinari
Hung, Hung
Huang, Su-Yun
contents Over the years, numerous rank estimators for factor models have been proposed in the literature. This article focuses on information criterion-based rank estimators and investigates their consistency in rank selection. The gap conditions serve as necessary and sufficient conditions for rank estimators to achieve selection consistency under the general assumptions of random matrix theory. We establish a unified theorem on selection consistency, presenting the gap conditions for information criterion-based rank estimators with a unified formulation. To validate the theorem's assertion that rank selection consistency is solely determined by the gap conditions, we conduct extensive numerical simulations across various settings. Additionally, we undertake supplementary simulations to explore the strengths and limitations of information criterion-based estimators by comparing them with other types of rank estimators.
format Preprint
id arxiv_https___arxiv_org_abs_2407_19959
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Information Criterion-Based Rank Estimation Methods for Factor Analysis: A Unified Selection Consistency Theorem and Numerical Comparison
Morimoto, Toshinari
Hung, Hung
Huang, Su-Yun
Statistics Theory
Over the years, numerous rank estimators for factor models have been proposed in the literature. This article focuses on information criterion-based rank estimators and investigates their consistency in rank selection. The gap conditions serve as necessary and sufficient conditions for rank estimators to achieve selection consistency under the general assumptions of random matrix theory. We establish a unified theorem on selection consistency, presenting the gap conditions for information criterion-based rank estimators with a unified formulation. To validate the theorem's assertion that rank selection consistency is solely determined by the gap conditions, we conduct extensive numerical simulations across various settings. Additionally, we undertake supplementary simulations to explore the strengths and limitations of information criterion-based estimators by comparing them with other types of rank estimators.
title Information Criterion-Based Rank Estimation Methods for Factor Analysis: A Unified Selection Consistency Theorem and Numerical Comparison
topic Statistics Theory
url https://arxiv.org/abs/2407.19959