出於模型的須要,咱們的團隊選擇作一次因子分析,一般這部分在隊伍中是會有同窗專門負責這塊的,至於爲何筆者就不在這裏多說了。code
在MATLAB中封裝了有關因子分析的方法--factoran
,讀者能夠經過help
命令來查看如何調用這個方法。get
須要讀者注意的是,factoran方法並不會作數據規範化,因此讀者須要本身來作這個操做。it
%數據單位化 TX_F_D=zscore(TX_D) %5,求和 SUM_F_D=TX_F_D+AZ_F_D+CA_F_D+NM_F_D %6,因子分析 [SUM_lambda,SUM_psi,SUM_T,SUM_stats,SUM_F]=factoran(SUM_F_D,6) %求取貢獻率 SUM_Contribute=Factor_Contribute(SUM_lambda,index) %求各項因子的得分 ALL_F=Factor_F(TX_F_D,AZ_F_D,CA_F_D,NM_F_D,SUM_lambda,SUM_Contribute) %畫圖 subplot(2,2,1) plot(YEARS,ALL_F{1}(:,1),'r-',YEARS,ALL_F{2}(:,1),'g--',YEARS,ALL_F{3}(:,1),'b:',YEARS,ALL_F{4}(:,1)) xlabel('YEARS') ylabel('F1') legend('TX','AZ','CA','NM','Location','SouthEast') %畫單個的圖 figure plot(YEARS,ALL_F{1}(:,1),'r-',YEARS,ALL_F{2}(:,1),'g--',YEARS,ALL_F{3}(:,1),'b:',YEARS,ALL_F{4}(:,1)) xlabel('YEARS') ylabel('F1') legend('TX','AZ','CA','NM','Location','SouthEast') figure plot(YEARS,ALL_F{1}(:,2),'r-',YEARS,ALL_F{2}(:,2),'g--',YEARS,ALL_F{3}(:,2),'b:',YEARS,ALL_F{4}(:,3)) xlabel('YEARS') ylabel('F2') legend('TX','AZ','CA','NM','Location','SouthEast') figure plot(YEARS,ALL_F{1}(:,3),'r-',YEARS,ALL_F{2}(:,3),'g--',YEARS,ALL_F{3}(:,3),'b:',YEARS,ALL_F{4}(:,3)) xlabel('YEARS') ylabel('F3') legend('TX','AZ','CA','NM','Location','SouthEast') figure plot(YEARS,ALL_F{1}(:,4),'r-',YEARS,ALL_F{2}(:,4),'g--',YEARS,ALL_F{3}(:,4),'b:',YEARS,ALL_F{4}(:,4)) xlabel('YEARS') ylabel('F') legend('TX','AZ','CA','NM','Location','SouthEast')
因爲結果有多種多樣的,直接給出MATLAB的工做空間,有興趣的讀者能夠自行下載。io
連接 密碼:zffrast