Code covered by the BSD License  

Highlights from
The N-way Toolbox

• []=plotfac(Factors,H,Axis0,Ax... PLOTFAC Plot the contents of Factors
• B=unimodal(X,Y,Bold) UNIMODAL unimodal regression
• B=unimodalcrossproducts(XtX,X... UNIMODALCROSSPRODUCTS
• C=ckron(A,B) CKRON
• G=T3core(X,Load,Weights,NonNe... T3CORE calculate Tucker core
• G=neye(Fac); NEYE Produces a super-diagonal array
• Options=setopts(Model); SETOPTS
• XCorr=SetNaNs1(X,ExMin,ExMax,... SETNANS1 fluorescence artifact treatment
• [A,B,C,D,E,F,G,H,I,J,K,L,M,N,... FAC2LET Convert 'Factors' to component matrices
• [A,B,C,fit]=dtld(X,F,SmallMod... DTLD direct trilinear decomposition
• [A,B,C]=gram(X1,X2,F); GRAM generalized rank annihilation method
• [A]=cmatrep(A,crit,v1,v2) CMATREP optimized matrep
• [Comb,ExplVariat]=explcore(G,... EXPLCORE For interpretation of cores and arrays
• [Consistency,G,stdG,Target]=c... CORCOND Core consistency for PARAFAC model
• [DIA_Rel,DIA_Abs]=CoreDian(C) COREDIAN Calculates core diagonality
• [E]=GSM(V); GSM orthogonalization
• [F,SS]=nonneg(X,M,F,Options); NONNEG1 alternative to NNLS
• [Factors,G,ExplX,Xm]=tucker(X... TUCKER multi-way tucker model
• [Factors,it,err,corcondia]=pa... PARAFAC multiway parafac model
• [Factors]=ini(X,Fac,MthFl,Ign... INI initialization of loadings
• [Factors]=inituck(X,Fac,MthFl... INITUCK initialization of loadings
• [G]=calcore(X,Factors,Options... CALCORE Calculate the Tucker core
• [Gv,ORot1,ORot2,ORot3]=maxdia... MAXDIA3 Maximize core diagonality
• [Gv,ORot1,ORot2,ORot3]=maxswd... MAXSWD3 maximize core slice-wise diagonality
• [Gv,ORot1,ORot2,ORot3]=maxvar... MAXVAR3 maximize core squared variance
• [IndicesN]=Two2N(DimX,Indices... TWO2N Conversion of indices between unfoldings and N-way arrays
• [R,Y]=complpol(X); COMPLPOL
• [SWD_Rel,SWD_Abs]=CoreSWDn(C) CORESWDN Calculates the 'core-slice-wise-diagonality'.
• [T,P]=fnipals(X,w,T) FNIPALS nipals algorithm for PCA
• [Var_Rel,Var_Abs]=CoreVarn(C) COREVARN Calculates the 'core-variance'
• [XValResult,Model]=ncrossreg(... NCROSSREG cross-validation of regression model
• [X]=missmult(A,B) MISSMULT product of two matrices containing NaNs
• [Xm]=nmodel(Factors,G,Om); NMODEL make model of data from loadings
• [Xnew,mX,sX]=nprocess(X,Cent,... NPROCESS pre and postprocessing of multiway arrays
• [Y,D]=normit(X) NORMIT normalize
• [Y]=Refold3(X,R); REFOLD3
• [b,All,MaxML]=ulsr(x,NonNeg);
• [b,B,AllBs]=monreg(x); MONREG monotone regression
• [i,j]=getindxn(R,Idx); GETINDXN
• [mm]=misssum(X,def) MISSSUM sum of a matrix X with NaN's
• [v]=nsetdiff(A,B); NSETDIFF
• [ypred,T,ssX,Xres]=npred(X,Fa... NPRED prediction with NPLS model
• dC=derdia3(C,n) DERDIA3 the derivative of the nth mode of the core
• dC=dervar3(C,n) DERVAR3 for core rotations
• eemtimize(X,maxlv); EEMTIMIZE
• fastnnls(XtX,Xty,tol) FASTNNLS Fast version of built-in NNLS
• kr(A,B); KR Khatri-Rao product
• krb(A,B); KRB Khatri-Rao product
• load=pfls(ZtZ,ZtX,dimX,cons,O... PFLS
• mm=missmean(X) MISSMEAN mean of a matrix X with NaN's
• ncosine(factor1,factor2); NCOSINE multiple cosine/Tuckers congruence coefficient
• ncrossdecomp(Method,X,FacMin,... NCROSSDECOMP crossvalidation of PARAFAC/Tucker/PCA
• ncrossdecomp(Method,X,FacMin,... NCROSSDECOMP crossvalidation of PARAFAC/Tucker/PCA
• nident(J,order,mag); NIDENT make 'identity' multi-way array
• npls(X,Y,Fac,show); NPLS multilinear partial least squares regression
• nshape.m
• ntimes(X,Y,modeX,modeY); NTIMES Array multiplication
• pfplot(X,Factors,Weights,Opti... PFPLOT plot parafac model
• pftest(NumRep,X,Fac,Options,c... PFTEST find the number of PARAFAC components
• st=stdnan(X); STDNAN estimate std with NaN's
• tbxStruct=demos DEMOS Demo list for The N-way Toolbox for MATLAB
• tucktest(varargin) TUCKTEST makes a scree-plot for Tucker using from [1 1 1] to Fac models
• contents.m
• derswd3.m
• fnnls.m
• parademo.m
• ppp.m
• tuckdemo.m
• tucker2.m
• View all files