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1、資料分析(第十週)10-6因子分析(FactorAnalysis)主成份(principalcomponent)分析是因子分析的一個特例,在此特例中,前面幾個主成份即為選定之共同因子。(A)定義:eigenvectorofeigenvalue則,(B)在(A)中即為主成份分析:尋找使得=有最大的變異且在(B)中,共同因子,尋找使得第一個共同因子貢獻最大變異,此變異(Communality)應(yīng)為。但在PC中變異已標準化至1,故將在PC中係數(shù)改變至。6資料分析(第十週)10-6而定義共同因子f1即為Y1,而其係數(shù)為取前面m個PC
2、當作共同因子,則,where共同因子模式即共同因子,特有因子,:loadingofithobservationonthejthcommonfactor則X之Variance-Covariancematrix,一般假設(shè)(1)共同因子在分解成為:主要分解的變異部份為:共同因子所能解釋的部份:communality。(2)若T為一orthogonalmatrix,where,6資料分析(第十週)10-6且,,在因子分析中可旋轉(zhuǎn)至任一軸,使得共同因子容易解釋,經(jīng)旋轉(zhuǎn)後之共同解釋變異部份不變。一般步驟為先固定communalities
3、為SMC(squaredmultiplecorrelation)即所得之作為communality(diagonal部份之值)此時Var-Covmatrix成為(ReducedCorrelationMatrix)依照PC做法並旋轉(zhuǎn)使得係數(shù)(loading)之variance為最大(此種旋轉(zhuǎn)稱為Varimax),但此時矩陣不一定為正定,故eigenvalue可能出現(xiàn)負值。資料分析講義:因子分析FactorAnalysisoptionsnodatenonotesps=60;datafactor1;inputpopschoolem
4、ployservicehouse;cards;570012.8250027025000100010.9600101000034008.81000109000380013.6170014025000400012.816001402500082008.326006012000120011.44001016000910011.533006014000990012.5340018018000960013.736003902500096009.633008012000940011.4400010013000;procfactordat
5、a=factor1;run;procfactorprior=smcdata=factor1preplotrotate=varimaxreorderplot;run;InitialFactorMethod:PrincipalComponentsPriorCommunalityEstimates:ONEEigenvaluesoftheCorrelationMatrix:Total=5Average=16資料分析(第十週)10-6EigenvalueDifferenceProportionCumulative12.87331359
6、1.076653500.57470.574721.796660091.581823210.35930.934030.214836890.114902830.04300.977040.099934050.084678680.02000.996950.015255370.00311.00002factorswillberetainedbytheMINEIGENcriterion.FactorPatternFACTOR1FACTOR2POP0.580960.80642SCHOOL0.76704-0.54476EMPLOY0.672
7、430.72605SERVICE0.93239-0.10431HOUSE0.79116-0.55818VarianceexplainedbyeachfactorFACTOR1FACTOR22.8733141.796660FinalCommunalityEstimates:Total=4.669974POPSCHOOLEMPLOYSERVICEHOUSE0.9878260.8851060.9793060.8802360.937500InitialFactorMethod:PrincipalFactorsPriorCommuna
8、lityEstimates:SMCPOPSCHOOLEMPLOYSERVICEHOUSE0.9685920.8222850.9691810.7857240.847019EigenvaluesoftheReducedCorrelationMatrix:Total=4.39280116Aver