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Bayesian Inference for ARFIMA Models by Sid Ahmed Mein is a document available to read on EtoBox.
What is Bayesian Inference for ARFIMA Models about?
The article presents a systematic Bayesian framework for the simultaneous inference of long-range dependence (LRD) and heavy-tail distribution parameters in ARFIMA models. It highlights the importance of accurately estimating these parameters, which are often biased when estimated separately. The proposed method demonstrates effectiveness on synthetic data and real-world solar X-ray time series data, allowing for flexible choice of heavy-tailed distributions.
- Author
- Sid Ahmed Mein
- Language
- EN