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Highlights from
The N-way Toolbox

[]=plotfac(Factors,H,Axis0,Ax... PLOTFAC Plot the contents of Factors
AB=ppp(A,B);
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]=nonneg1(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=derswd3(C,n) DERSWD3 for core rotations
dC=dervar3(C,n) DERVAR3 for core rotations
fastnnls(XtX,Xty,tol) FASTNNLS Fast version of built-in NNLS
fastnnls(x,y,tol,b)
kr(A,B); KR 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
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
varargout=nshape(X,f); NSHAPE rearrange a multi-way array
contents.m
dorritmakedata.m
parademo.m
tuckdemo.m
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4.4 | 10 ratings Rate this file 38 Downloads (last 30 days) File Size: 5.19 MB File ID: #1088

The N-way Toolbox

by Rasmus Bro

22 Nov 2001 (Updated 07 Jul 2009)

Tools for fitting multi-way (tensor) models such as PARAFAC

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Description

The N-way Toolbox for MATLAB is the most advanced toolbox for fitting multi-way models. It is free and provides means for fitting PARAFAC, Tucker, N-PLS, GRAM and TLD. Further updates and data sets are available at http://www.models.life.ku.dk/

A related function is "parafac2", also available on the File Exchange.

MATLAB release

MATLAB 7.2 (R2006a)

Tags for This File
Everyone's Tags	chemometrics, gram, multiway(2), npls(2), parafac, partial least squares, pls, probability, statistics, threeway, trilinear, tucker3
Tags I've Applied
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Comments and Ratings (11)
27 Aug 2003	Sangdon Lee	Excellent for PCA and PLS and N-way analysis.
28 Oct 2003	david stanley	Outstanding!
18 Feb 2004	Luis Mesa
23 Mar 2004	Matheus Freitas	Require high virtual memory
24 May 2004	ROYA MIRZAJANI
28 Apr 2005	friend ass	good enough
05 Apr 2006	Dr. Michael Griffiths	An excellent package, well laid out, a clearly explained tutorial section and clearly presented results on-screen.
10 Nov 2006	shaohua hu	well done!
27 Nov 2006	alireza mohammadpour	complet
25 Dec 2008	USTC Lawrence
05 Jan 2012	Drel

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Updates
07 Jan 2009	Bugs removed and files updated to version 7 of matlab
08 Jan 2009	bugs fixed and files updated to current matlab version
05 Jul 2009	Deleted obsolete copyright notes in m-files
07 Jul 2009	Removed license information

Tag Activity for this File
Tag	Applied By	Date/Time
statistics	Rasmus Bro	22 Oct 2008 06:39:30
probability	Rasmus Bro	22 Oct 2008 06:39:30
parafac	Rasmus Bro	22 Oct 2008 06:39:30
multiway	Rasmus Bro	22 Oct 2008 06:39:30
trilinear	Rasmus Bro	22 Oct 2008 06:39:30
threeway	Rasmus Bro	22 Oct 2008 06:39:30
tucker3	Rasmus Bro	22 Oct 2008 06:39:30
gram	Rasmus Bro	22 Oct 2008 06:39:30
npls	Rasmus Bro	22 Oct 2008 06:39:30
npls	Courosh	02 Sep 2010 19:16:03
pls	Ken Purchase	28 Jul 2011 21:18:23
chemometrics	Ken Purchase	28 Jul 2011 21:18:23
partial least squares	Ken Purchase	28 Jul 2011 21:18:23
multiway	Veronique	20 Oct 2011 11:28:26

Highlights from The N-way Toolbox

The N-way Toolbox

Highlights from
The N-way Toolbox