Empirical Bayes interpretations of random point events
Empirical Bayes interpretations of random point events
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DOI：
10.1088/0305-4470/38/29/l04
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发表时间：
2005-07-22
期刊：
影响因子：
--
通讯作者：
Shinomoto, S
中科院分区：
文献类型：
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作者：
Koyama, S;Shinomoto, S
给定一系列明显随机的点事件，如神经元的尖峰脉冲，人们可以将它们解释为在时间上不规则地从恒定速率或规则地从波动速率导出。为了确定在任何给定情况下哪种解释更合理，我们采用经验贝叶斯方法。对于一个序列的点事件来自一个速率波动的伽马过程，边际似然函数可以拥有两个局部最大值和系统表现出一阶相变表示开关的最合理的解释从一个到另一个。
Given a sequence of apparently random point events, such as neuronal spikes, one may interpret them as being derived either irregularly in time from a constant rate or regularly from a fluctuating rate. To determine which interpretation is more plausible in any given case, we employ the empirical Bayes method. For a sequence of point events derived from a rate-fluctuating gamma process, the marginal likelihood function can possess two local maxima and the system exhibits a first-order phase transition representing the switch of the most plausible interpretation from one to the other.