伴随着这个,又有了使用的数据分析新方法,例如,马尔科夫链,蒙特卡洛模拟这些大型计算机密集型算法。
Accompanying this have been new approaches to data analysis using, for example, Markov Chain Monte Carlo simulations that are hugely computer intensive.
该模型的核心部分是根据观测到的资料,通过蒙特卡洛马尔科夫链随机抽样的方法来估计变点位置的后验概率分布。
Given the observed hydrological data, the model can estimate the posterior probability distribution of each location of change-point by using the Monte Carlo Markov Chain (MCMC) sampling method.
本文提出了一个基于蒙特卡洛-马尔科夫链方法的随机模型生成方法,以产生准则函数值最小的备选模型。
In this paper I suppose an MCMC random model generating procedure that can generate a model with the lowest criterion value.
本文提出了一个基于蒙特卡洛-马尔科夫链方法的随机模型生成方法,以产生准则函数值最小的备选模型。
In this paper I suppose an MCMC random model generating procedure that can generate a model with the lowest criterion value.
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