Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models

Bayesian Inference on the Memory Parameter for Gamma-Modulated Regression Models

In this work, we propose a Bayesian methodology to make inferences for the memory parameter and other characteristics under non-standard assumptions for a class of stochastic processes. This class generalizes the Gamma-modulated process, with trajectories that exhibit long memory behavior, as well a...

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Bibliographic Details
Main Authors: Plinio Andrade, Laura Rifo, Soledad Torres, Francisco Torres-Avilés
Format: Article
Language:English
Published: MDPI AG 2015-09-01
Series:Entropy
Subjects:
Gamma-modulated process
long memory
Bayesian inference
approximate Bayesian computation
MCMC algorithm
e-value
Online Access:http://www.mdpi.com/1099-4300/17/10/6576

Internet

http://www.mdpi.com/1099-4300/17/10/6576

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