The esaBcv package provides functions to estimate the latent factors of a given
matrix, no matter it is high-dimensional or not. It tries to first estimate the
number of factors using Bi-cross-validation and then estimate the latent factor
matrix and the noise variances using an Early-stopping-alternation method.
The method is proposed by Art B. Owen and Jingshu Wang (2015).