Robust Covariance Matrix Estimation for High-Dimensional Compositional Data with Application to Sales Data Analysis
高维成分数据的稳健协方差估计及销售数据应用
Compositional data arises in a wide variety of research areas when some form of standardization and composition is necessary. Estimating covariance matrices is of fundamental importance for high-dimensional compositional data analysis. However, existing methods require the restrictive Gaussian or sub-Gaussian assumption, which may not hold in practice. We propose a robust composition adjusted thresholding covariance procedure based on Huber-type M-estimation to estimate the…