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贝叶斯相关系数估计AI 解读

We propose prior probability models for variance‐covariance matrices in order to address two important issues. First, the models allow a researcher to represent substantive prior information about the strength of correlations among a set of variables. Secondly, even in the absence of such information, the increased flexibility of the models mitigates dependence on strict parametric assumptions in standard prior models. For example, the model allows a posteriori different…

切换扩散模型的马尔可夫链蒙特卡洛方法AI 解读

Reversible jump Metropolis–Hastings updating schemes can be used to analyse continuous‐time latent models, sometimes known as state space models or hidden Markov models. We consider models where the observed process X can be represented as a stochastic differential equation and where the latent process D is a continuous‐time Markov chain. We develop Markov chain Monte Carlo methods for analysing both Markov and non‐Markov versions of these models. As an illustration of how…