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arfima模型参数贝叶斯估计的渐近性质(英文)

, PP. 16-22

Keywords: 贝叶斯方法,arfima模型,后验分布,渐近性质

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Abstract:

首先根据贝叶斯定理得到arfima模型参数的后验边缘分布,并选择后验边缘分布的众数作为参数的估计值.参照季节性arfima模型的极大似然估计的渐近性质的证明思路,证明了模型参数的贝叶斯估计具有相合性、有效性和渐近正态性.最后,对参数的贝叶斯估计方法的大样本性质进行仿真模拟,结果表明当时间序列样本足够大时,参数的估计值越来越接近于真实值.

References

[1]  jeffreyspa,inalinir.bayesiananalysisofautoregressivefractionallyinintegratedmoving-averageprocesses[j].journaloftimeseriesanalysis,1995,19(1):99-111.
[2]  grangercwj,joyeuxr.anintroductiontolong-memorytimeseriesmodelsandfractionaldifferencing[j].journaloftimeseriesanalysis,1980,1(1):15-39.
[3]  channh.estimationoflong-memorytimeseries:asurveyoflikelihood-basedmethods[j].advancesineconometrics,2006,20(2):89-121.
[4]  hannanej.theasymptotictheoryoflineartime-seriesmodels[j].journalofappliedprobability,1973,10(4):913.
[5]  changxuejiang,chenming,wangmingsheng.timeseriesanalysis[m].beijing:chinahighereducationpress,1993.
[6]  palmaw,channh.efficientestimationofseasonallong-dependentprocesses[j].journaloftimeseriesanalysis,2005,26(6):864-891.
[7]  dahlhausr.efficientparameterestimationforsel-fsimilarprocesses[j].theannalsofstatistics,1989,17(4):1749-1766.
[8]  taniguchim,kakizaway.asymptotictheoryofstatisticalinferencefortimeseries[m].newyork:springer-verlag,2000.
[9]  graybiufa.matriceswithapplicationsinstatistics[m].2nded.belmont,ca:wadsworth,1983.

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