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• W2072228362 abstract "ABSTRACTIn this work, we propose a method for estimating the Hurst index, or memory parameter, of a stationary process with long memory in a Bayesian fashion. Such approach provides an approximation for the posterior distribution for the memory parameter and it is based on a simple application of the so-called approximate Bayesian computation (ABC), also known as likelihood-free method. Some popular existing estimators are reviewed and compared to this method for the fractional Brownian motion, for a long-range binary process and for the Rosenblatt process. The performance of our proposal is remarkably efficient." @default.
• W2072228362 created "2016-06-24" @default.
• W2072228362 creator A5029131552 @default.
• W2072228362 creator A5051068933 @default.
• W2072228362 date "2016-11-04" @default.
• W2072228362 modified "2023-10-01" @default.
• W2072228362 title "Long-range dependence and approximate Bayesian computation" @default.
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• W2072228362 doi "https://doi.org/10.1080/03610918.2014.995816" @default.
• W2072228362 hasPublicationYear "2016" @default.
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