Estimation of the Hurst exponent from noisy data: a Bayesian approach
Estimation of the Hurst exponent from noisy data: a Bayesian approach
复制标题
从噪声数据估计赫斯特指数：贝叶斯方法
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
M. Holschneider
中科院分区：
文献类型：
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作者：
N. Makarava;M. Holschneider
We consider a model based on the fractional Brownian motion under the influence of noise. We implement the Bayesian approach to estimate the Hurst exponent of the model. The robustness of the method to the noise intensity is tested using artificial data from fractional Brownian motion. We show that estimation of the parameters achieved when noise is considered explicitly in the model. Moreover, we identify the corresponding noise-amplitude level that allow to receive the correct estimation of the Hurst exponents in various cases.
影响因子：
2.4
作者：
Hu, K;Ivanov, PC;Stanley, HE
通讯作者：
Stanley, HE
影响因子：
2.1
作者：
Hausdorff, Jeffrey M.
通讯作者：
Hausdorff, Jeffrey M.