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1、www.pudn.com>mssa.rar>EEOF.Mfunction[E,V,A,C]=eeof(X,M,convert)%Syntax:[E,V,A,C]=eeof(X,M);[E,V,A,C]=eeof(X,M,1);%Thisfunctionperformsanextendedempiricalorthogonal%function(EEOF)analysisofmatrix'X',forembeddingdimension'M'.%EachoftheLcolumnsofXisatim
2、eseriesoflengthN.%%Returns:E-eigenfunctionmatrix.(LMbyLM)%V-vectorcontainingvariances(unnormalizedeigenvalues).%A-matrixofprincipalcomponents.%C-lag-covariancematrix.%%Visorderedfromlargetosmall:EandAaresortedaccordingly.%%NotethatXisassumedtobecente
3、red.Tocenterthedata,use%thecommands:%[r,c]=size(X);X=X-ones(r,1)*mean(X);beforerunningEEOF.%Ifyoualsowanttostandardizethedata,use:%X=X./(ones(r,1)*std(X));.%%Ifathirdargumentissupplied,theeigenfunctions/valueswill%bereorderedintothesameformatasMSSAou
4、tput-i.e.Lblocks%ofsizeMratherthanMblocksofsizeL.%%Thisfunctionprovidesthesameoutput,withinnumericallydetermined%limits,asMSSAmethodsusingBroomhead-Kingtypecovarianceestimation:%itisintendedasacheckonthosefunctions.%%Notethatthisfunctionis*extremely*
5、computationallyintensive%forlargematricesandlags.Forexample,ifXis1000by1000,%andM=5,EEOFwilltakeabout10hoursonaCrayYMP!Inputting%asubsetofthePCsofXratherthanthefulldatamatrixcan%substantiallyreducethecomputationalload.%%WrittenbyEricBreitenberger.Ver
6、siondate1/11/96%Pleasesendcommentsandsuggestionstoeric@gi.alaska.edu%[N,L]=size(X);ifM*L>=N-M+1,disp('Warning:Covariancematrixmaybeill-conditioned.'),end%Createtheextendedmatrix:T=zeros(N-M+1,M*L);fori=1:MT(:,L*(i-1)+1:L*i)=X(i:N-M+i,:);end%Computeth
7、eeigenvectors/valuesofthecovariancematrix:C=(T'*T)/(N-M+1);clearX[E,V]=eig(C);V=diag(V);A=T*E;%computeprincipalcomponentsifnargin==3%PrepareMSSA-styleoutput:%sortE,V,C,andAfromMblocksofLtoLblocksofM.ind=1:L:(M-1)*L+1;fori=1:L,index=[indexind+i-1];end
8、E=E(index,index);V=V(index);%sortthecovariancematrixandPCs:C=C(index,index);A=A(:,index);end%Sorteigenvalues/vectors/PCsindescendingorder:[V,ind]=sort(-V);V=-V';E=E(:,ind);A=A(:,ind);窗體底端www.pudn.com>mssa.rar>EOF.Mfunction[F,L,B]=eof(X,n,s);%EOFcalcu
