非平稳时间序列的多重分析时间加权去趋势偏互相关分析

《非平稳时间序列的多重分析时间加权去趋势偏互相关分析》由会员上传分享，免费在线阅读，更多相关内容在学术论文-天天文库。

1、Æ“Ò10530ÆÒ201510111130©aÒO157.5—?úma¬ÆØ©š²•žmSõ•©/žmª³pƒ'©ÛÆž<':•“’yIÇƶ¡êƆOŽ‰ÆÆƉ;’êÆïÄ••)Ô†‚¸&E?n"˜lco›Fš²•žmSõ•©/žmª³pƒ'©ÛÆž<':“6¶9…¡’yIÇƶ¡êƆOŽ‰ÆÆƉ;’êÆïÄ••)Ô†‚¸&E?nÆž?OnÆa¬Æǃü‰ŒÆØ©JFÏ2018-4-10Multifractaltemporallyweighteddetrendedpartialcross-

2、correlationanalysisofnonstationarytimeseriesCandidateDianyiLingSupervisorandRankProfessorZuGuoYuCollegeSchoolofMathematicsandComputationalScienceProgramMathematicsSpecializationBiologicalandEnvironmentalInformationProcessingDegreeMasterofScienceUniversityXiangtanUniversityDateApri

3、l10th,2018Á‡
ÓσrK•E,g,¬XÚ¥ÓžP¹ü‡pƒ'žmSž§3Ø•Äùd3󧆦^ª³pƒ'©Ûœ¹e§(J¬k¤"©Äuõ•©/žmª³pƒ'©Û(MF-TWXDFA)Úõ•©/ª³pƒ'©Û(MF-DPXA)§Jј«#•{

4、õ•©/žmª³pƒ'©Û(MF-TWDPCCA)"TŽ{M#3u?nÉ
ÓåK•ü^žmSž§Úƒ'©Û§±•xžØÙ{d3žmSK•§ü^žmSƒmý¢pƒ'5§=pƒ'5"·‚ÏLêŠ[§y²MF-TWDPCCApƒ'Xê'MF-DPXApƒ'

5、Xê•k`³"•?˜ÚЫõ•©/žmª³pƒ'©Û(MF-TWDPCCA)Ž{^§·‚ÏLêŠ[é•ýS?1•©/5Ÿ©Û§uyMF-TWDPCCAŽ{U«Ûõ3ü^žmSƒmý¢pƒ'5£pƒ'5¤§MF-TWXDFA™U‰§ù•`²3©ÛÉ
ÓåK•ü^š²•žmSƒ'5ž§?1pƒ'©Û´ék7‡"'…cµpƒ'5¶õ•©/žmª³pƒ'©Û(MF-TWDPCCA)¶MF-TWDPCCApƒ'XêIAbstractWhencommonfactorsstronglyin uencetwocross-correl

6、atedtimeseriesrecordedincomplexnaturalandsocialsystems,theresultswillbebiasedifweusedetrendedcross-correlationanalysiswithoutconsideringthesecommonfac-tors.Anewmethod

7、multifractaltemporallyweighteddetrendedpartialcross-correlationanalysis(MF-TWDPCCA)whichisbasedonmultifractaltempo

8、ral-lyweighteddetrendedcross-correlationanalysis(MF-TWXDFA)andmultifrac-talpartialcross-correlationanalysis(MF-DPXA)isproposedinthisthesis.Theinnovationofthisalgorithmistointroducepartialcorrelationanalysistodealwithtwotimeserieswhichareaectedbythecommonexternalforces.WeuseMF-TWD

9、PCCAtodepicttheintrinsiccross-correlationsbetweenthetwosimul-taneouslyrecordedtimeseriesafterremovingtheeectsofotherpotentialtimeseries.NumericalsimulationdemonstratethatMF-TWDPCCApartialcorrelationcoecientismoreadvantageousthanMF-DPXA.TofurthershowtheutilityofMF-TWDPCCA,weuseit

10、toinvestigatemultifractaltimeseri