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Author (up) Araya, H.; Plaza-Vega, F. doi  openurl
  Title Parameter estimation for fractional power type diffusion: A hybrid Bayesian-deep learning approach Type
  Year 2023 Publication Communications In Statistics-Theory And Methods Abbreviated Journal Commun. Stat.-Theory Methods  
  Volume Early Access Issue Pages  
  Keywords Parameter estimation; power-type fractional diffusion; fractional Brownian motion; ABC  
  Abstract In this article, we consider the problem of parameter estimation in a power-type diffusion driven by fractional Brownian motion with Hurst parameter in (1/2,1). To estimate the parameters of the process, we use an approximate bayesian computation method. Also, a particular case is addressed by means of variations and wavelet-type methods. Several theoretical properties of the process are studied and numerical examples are provided in order to show the small sample behavior of the proposed methods.  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
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  Series Volume Series Issue Edition  
  ISSN 0361-0926 ISBN Medium  
  Area Expedition Conference  
  Notes WOS:001120573700001 Approved  
  Call Number UAI @ alexi.delcanto @ Serial 1919  
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