| dc.creator | Andrade | |
| dc.creator | P.; Rifo | |
| dc.creator | L. | |
| dc.date | 2017 | |
| dc.date | 2017-11-13T13:56:50Z | |
| dc.date | 2017-11-13T13:56:50Z | |
| dc.date.accessioned | 2018-03-29T06:10:09Z | |
| dc.date.available | 2018-03-29T06:10:09Z | |
| dc.identifier | Communications In Statistics-theory And Methods. Taylor & Francis Inc, v. 46, p. 1219 - 1237, 2017. | |
| dc.identifier | 0361-0918 | |
| dc.identifier | 1532-4141 | |
| dc.identifier | WOS:000395194600027 | |
| dc.identifier | 10.1080/03610918.2014.995816 | |
| dc.identifier | http://www.tandfonline.com/doi/abs/10.1080/03610918.2014.995816 | |
| dc.identifier | http://repositorio.unicamp.br/jspui/handle/REPOSIP/329945 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/1366970 | |
| dc.description | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.description | In 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. | |
| dc.description | 46 | |
| dc.description | 2 | |
| dc.description | 1219 | |
| dc.description | 1237 | |
| dc.description | Sao Paulo Research Foundation [2013/07699-0] | |
| dc.description | CNPq at the University of Sao Paulo [141048/2013-1] | |
| dc.description | Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) | |
| dc.description | Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) | |
| dc.language | English | |
| dc.publisher | Taylor & Francis Inc | |
| dc.publisher | Philadelphia | |
| dc.relation | Communications in Statistics-Theory and Methods | |
| dc.rights | fechado | |
| dc.source | WOS | |
| dc.subject | Bayesian Inference | |
| dc.subject | Entropy | |
| dc.subject | Hurst Index | |
| dc.subject | Likelihood-free Method | |
| dc.subject | Long-range Dependence | |
| dc.title | Long-range Dependence And Approximate Bayesian Computation | |
| dc.type | Artículos de revistas | |
