A note on statistical analysis of factor models of high dimension

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 models. Their based on a critical assumption: The error variance estimators uniformly bounded probability. Instead making such an assumption, we provide rigorous proof this result under some mild conditions.