Parameter estimation for fractional power type diffusion: A hybrid Bayesian-deep learning approach
Keywords: parameter estimation, abc, fractional brownian motion, power-type fractional diffusion
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.
Más información
| Título según WOS: | Parameter estimation for fractional power type diffusion: A hybrid Bayesian-deep learning approach |
| Título de la Revista: | COMMUNICATIONS IN STATISTICS-THEORY AND METHODS |
| Volumen: | 53 |
| Número: | 22 |
| Editorial: | PHILADELPHIA |
| Fecha de publicación: | 2024 |
| Página de inicio: | 8234 |
| Página final: | 8254 |
| Idioma: | English |
| DOI: |
10.1080/03610926.2023.2280522 |
| Notas: | ISI |