MODELING AND PREDICTION CONCERNING TIME SERIES OF FLOOD/DROUGHT RUNS USING THE SELF-EXCITING THRESHOLD AUTOREGRESSIVE MODEL-中国期刊网

摘要 WhenlinearregressivemodelssuchasARorARMAmodelareusedforfittingandpredictingclimatictimeseries,resultsareoftennotsufficientlygoodbecausenonlinearvariationsinthetimeseries.Inthispaper,anonlinearself-excitingthresholdautoregressive(SETAR)modelisappliedtomodelingandpredictingthetimeseriesofflood/droughtrunsinBeijing,whichwerederivedfromthegradedhistoricalflood/droughtrecordsinthelast511years(1470—1980).TheresultsshowthatthemodelingandpredictingwiththeSETARmodelaremuchbetterthanthatoftheARmodel.Thelattercanpredicttheflood/droughtrunswithalengthonlylessthantwoyears,whiletheformalcanpredictmorethanthree-yearlengthruns.ThismaybeduetothefactthattheSETARmodelcanrenewthemodelaccordingtotherun-turningpointsintheprocessofpredic-tion,thoughthetimeseriesisnonstationary.

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MODELING AND PREDICTION CONCERNING TIME SERIES OF FLOOD/DROUGHT RUNS USING THE SELF-EXCITING THRESHOLD AUTOREGRESSIVE MODEL

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MODELING AND PREDICTION CONCERNING TIME SERIES OF FLOOD/DROUGHT RUNS USING THE SELF-EXCITING THRESHOLD AUTOREGRESSIVE MODEL

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