Bayesian analysis of autoregressive fractionally integrated moving-average processes

DOI10.1111/1467-9892.00079zbMath0902.62111OpenAlexW2062790716MaRDI QIDQ3838323

Ravishanker, Nalini, Jeffrey S. Pai

Publication date: 14 December 1998

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/1467-9892.00079

zbMATH Keywords

time seriesposterior distributionMarkov chain Monte Carlo methodsGibbs samplingexact likelihoodlong-memory models

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15)

Related Items (12)

Modelling structural breaks, long memory and stock market volatility: an overview ⋮ Bayesian analysis of long memory and persistence using ARFIMA models ⋮ Long memory and nonlinearities in realized volatility: a Markov switching approach ⋮ Bayesian estimation of Gegenbauer processes ⋮ Bayesian estimation of fractional difference parameter in ARFIMA models and its application ⋮ The ARMA alphabet soup: a tour of ARMA model variants ⋮ Data analysis using regression models with missing observations and long-memory: an application study ⋮ Likelihood‐based Analysis of a Class of Generalized Long‐Memory Time Series Models ⋮ Bayesian wavelet analysis of autoregressive fractionally integrated moving-average processes ⋮ BAYESIAN ANALYSIS OF A FRACTIONAL COINTEGRATION MODEL ⋮ First-order bias correction for fractionally integrated time series ⋮ Estimation methods for stationary Gegenbauer processes

This page was built for publication: Bayesian analysis of autoregressive fractionally integrated moving-average processes