我们接下来看一个有限维空间马尔可夫链的简单例子: Example: Predicting the weather with a finite state-space Markov chain 假如加州大学伯克利分校的天气有三种: 晴天,雾天和雨天(这用来模拟状态空间的三个离散的值)。这里的天气状态十分稳定,所以伯克利的天气预报员可以轻松地根据当前的天气来预测下周的天气,按照...
1. Introduction 第一次接触到 Markov Chain Monte Carlo (MCMC) 是在 theano 的 deep learning tutorial 里面讲解到的 RBM 用到了 Gibbs sampling,当时因为要赶着做项目,虽然一头雾水,但是也没没有时间仔细看。趁目前比较清闲,把 machine learning 里面的 sampling methods 理一理,发现内容还真不少,有些知识本...
Van Ravenzwaaij, D.; Cassey, P.; Brown, S. A simple introduction to Markov Chain Monte-Carlo sampling. Psychon. Bull. Rev. 2017. [CrossRef] [PubMed]van Ravenzwaaij, D., Cassey, P., & Brown, S. (this issue). A simple introduction to Markov chain Monte-Carlo sampling. Psychonomic...
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D. A simple introduction to Markov Chain Monte-Carlo sampling. Psychom. Bull. Rev. 25, 143–154 (2018). Article Google Scholar Agresti, A. & Hitchcock, D. B. Bayesian inference for categorical data analysis. Stat. Methods Appl. 14, 297–330 (2005). Article MathSciNet MATH Google ...
(two levels: 2- and 3-stimulus arrays), and their interactions; and a random effect of participant ID. However, this model resulted in a singular fit. We next built an equivalent Markov chain Monte Carlo GLMM in a Bayesian framework using theMCMCglmmpackage36. This model had the same ...
Starting from a real-valued Markov chain X0,X1,…,Xn with stationary transition probabilities, a random element {Y(t);t∈[0, 1]} of the function space D[0, 1] is constructed by letting Y(kn)=Xk, k= 0,1,…,n, and assuming Y (t) constant in between. Sample tightness criteria ...
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