On the Statistical Analysis of Smoothing by Maximizing Dirty Markov Random Field Posterior Distributions
通过最大化“脏”马尔可夫随机场后验进行平滑的统计分析
We consider Bayesian nonparametric function estimation using a Markov random field prior based on the Laplace distribution. We describe efficient methods for finding the exact maximum a posteriori estimate, which handle constraints naturally and avoid the problems posed by nondifferentiability of the posterior distribution; the methods also make links to spline and wavelet smoothers and to a dual posterior distribution. Three automatic smoothing parameter selection…