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Asymptotic Properties of Parametric Bayesian Estimation in ARFIMA Models(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2008年02期
Page:
16-22
Research Field:
数学
Publishing date:

Info

Title:
Asymptotic Properties of Parametric Bayesian Estimation in ARFIMA Models
Author(s):
Hong Zhaoping; Du Xiuli
School of Mathematics and Computer Science,Nanjing Normal University,Nanjing 210046,China
Keywords:
Bayes ian m ethods;  ARFIMA models;  poster io r d istr ibution;  asym ptotic prope rties
PACS:
O212.8
DOI:
-
Abstract:
Them arg inal po ster io r distr ibution of the param eter in theARFIMA m ode ls is presen ted by Bayes theo rem and the mode o f them arg inal posterior d istr ibu tion is choosed as the estim ator. Then, fo llow ed the analysis of the asympoto tic properties of max imum likelihood estim a tion fo r the seasonal ARFIMA m ode ls, the cons istency, e fficiency and asympto-t ic norma lity o f the Bayesian estima tor are prov ed. Fina lly, large sam ple perform ance o f the Bayesian estim ates is ex amined by sim ulations. It is shown that the estim ates behave we ll when the sam ple size is large enough.

References:

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Last Update: 2013-05-05