A note on statistical analysis of factor models of high dimension

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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.
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