Use this URL to cite or link to this record in EThOS:
Title: Bayesian inference of autoregressive models
Author: Kadir, Dler
ISNI:       0000 0004 7226 6764
Awarding Body: University of Sheffield
Current Institution: University of Sheffield
Date of Award: 2018
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Thesis embargoed until 15 Jan 2023
Access from Institution:
The principles, models and steps of Bayesian time series analysis and forecasting have been developed extensively during the past forty years. In order to estimate parameters of an autoregressive (AR) model we develop Markov chain Monte Carlo (MCMC) schemes for inference of AR model. It is our interest to propose a new prior distribution placed directly on the AR parameters of the model. Thus, we revisit the stationarity conditions to determine a flexible prior for AR model parameters.
Supervisor: Triantafyllopoulos, Kostas Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available