The article discusses how sample covariance matrices can differ from population covariance matrices in high-dimensional data. The researchers developed a new method using moments to estimate the population spectral distribution from sample covariance matrices. They showed that the estimator is accurate and can handle unknown model dimensions. Simulation experiments confirmed the effectiveness of the proposed approach.