REFA: Robust Exponential Factor Analysis
A robust alternative to the traditional principal component estimator is proposed within the framework of factor models, known as Robust Exponential Factor Analysis, specifically designed for the modeling of high-dimensional datasets with heavy-tailed distributions. The algorithm estimates the latent factors and the loading by minimizing the exponential squared loss function. To determine the appropriate number of factors, we propose a modified rank minimization technique, which has been shown to significantly enhance finite-sample performance.
||R (≥ 3.5.0)
||Jiaqi Hu [cre, aut],
Xueqin Wang [aut]
||Jiaqi Hu <hujiaqi at mail.ustc.edu.cn>
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