Goodness-of-fit tests for high-dimensional Gaussian graphical models via exchangeable sampling
通过可交换抽样检验高维高斯图模型的拟合优度
Abstract We introduce a general framework for testing goodness-of-fit for Gaussian graphical models in both the low- and high-dimensional settings. This framework is based on a novel algorithm for generating exchangeable copies by conditioning on sufficient statistics. This framework provides exact finite-sample error control regardless of the dimension and allows flexible choices of test statistics to improve power. We explore several candidate test statistics and conduct…