A note on statistical analysis of factor models of high dimension

Zhigen Gao, Jianhua Guo, Yanyuan Ma

Research output: Contribution to journalArticlepeer-review

Abstract

Linear factor models are familiar tools used in many fields. Several pioneering literatures established foundational theoretical results of the quasi-maximum likelihood estimator for high-dimensional linear factor models. Their results are based on a critical assumption: The error variance estimators are uniformly bounded in probability. Instead of making such an assumption, we provide a rigorous proof of this result under some mild conditions.

Original languageEnglish (US)
JournalScience China Mathematics
DOIs
StateAccepted/In press - 2021

All Science Journal Classification (ASJC) codes

  • Mathematics(all)

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