作者：Rohe, Karl; Zeng, Muzhe
摘要：In the 1930s, Psychologists began developing Multiple-Factor Analysis to decompose multivariate data into a small number of interpretable factors without any a priori knowledge about those factors. In this form of factor analysis, the Varimax factor rotation redraws the axes through the multi-dimensional factors to make them sparse and thus make them more interpretable. Charles Spearman and many others objected to factor rotations because the factors seem to be rotationally invariant. Despite ...
作者：Liu, Yang
作者单位：University System of Maryland; University of Maryland College Park
作者：Beraha, Mario; Griffin, Jim E.
作者单位：University of Turin; University of London; University College London
摘要：We propose a methodology for modelling and comparing probability distributions within a Bayesian nonparametric framework. Building on dependent normalised random measures, we consider a prior distribution for a collection of discrete random measures where each measure is a linear combination of a set of latent measures, interpretable as characteristic traits shared by different distributions, with positive random weights. The model is nonidentified and a method for postprocessing posterior sam...
