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物理学报. 2009, 58(9): 6050-6057.
doi: 10.7498/aps.58.6050.
海-气振子系统中未知参数的MCMC方法识别
- 收稿日期: 2009-01-15
- 修回日期: 2009-02-10
- 刊出日期: 2009-09-20
摘要: 利用MCMC方法对赤道东太平洋SST的海-气振子模型中未知参数进行识别.首先通过贝叶斯公式导出振子系统中参数的后验概率密度函数.然后采用自适应Metropolis算法构造未知参数的Markov链，截取收敛的样本序列估计参数值.数值试验结果表明：所提出的方法具有很高的估计精度，同时具有较好的抗噪声性能.
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关键词:
- 海-气振子 /
- 参数估计 /
- 马尔科夫链蒙特卡罗方法
English Abstract
Estimating parameters of air-sea oscillator with MCMC method
- Received Date:
15 January 2009
- Accepted Date:
10 February 2009
- Published Online:
20 September 2009
Abstract: The Markov chain Monte Carlo （MCMC） method is used to estimate the unknown parameters of air-sea oscillator system, which is a model of Eastern Pacific sea surface temperature （SST）. Firstly，the posterior probability density function for unknown parameters of air-sea oscillator system is deduced with the Bayesian formula. Secondly， the Adaptive Metropolis algorithm is used to construct the Markov Chains of unknown parameters. And the converged samples are used to calculate the mathematic expectation. The results of numerical experiments show that parameters estimated by the new method have high precision and the noise is filtered effectively from the observations.
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