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arXiv 1810.09682stat.AP
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使用非齐次隐马尔可夫模型的降水和温度的双变量模拟

Bivariate modelling of precipitation and temperature using a non-homogeneous hidden Markov model

Augustin Touron, Thi Thu Huong Hoang, Sylvie Parey

摘要:

为了生成真实的日平均气温和降水量二元过程的合成时间序列,我们引入了一个非齐次隐马尔可夫模型。非均匀性在于隐态之间的周期性转移概率和随时间变化的发射分布。这使得模型能够考虑天气变量的非平稳行为。通过仔细选择发射分布,也可以对两个变量之间的依赖结构进行建模。该模型被应用到几个气象站在欧洲的各种气候,我们表明,它是能够模拟现实的二元时间序列。

英文摘要:

Aiming to generate realistic synthetic times series of the bivariate process of daily mean temperature and precipitations, we introduce a non-homogeneous hidden Markov model. The non-homogeneity lies in periodic transition probabilities between the hidden states, and time-dependent emission distributions. This enables the model to account for the non-stationary behaviour of weather variables. By carefully choosing the emission distributions, it is also possible to model the dependance structure between the two variables. The model is applied to several weather stations in Europe with various climates, and we show that it is able to simulate realistic bivariate time series.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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