plot.PTAk: Plot a PTAk object

plot.PTAkR Documentation

Plot a PTAk object


Screeplot of singular values or superposed plot of modes for one or two components (1 dimensional scatterplot with spread labels or scatterplot on two dimensions).


## S3 method for class 'PTAk'
plot(x, labels = TRUE, mod = 1, nb1 = 1, nb2 = NULL,
    coefi = list(NULL, NULL), xylab = TRUE, ppch = (1:length(solution)),
    lengthlabels = 2, scree = FALSE, ordered = TRUE,
    nbvs = 40, RiskJack = NULL, method = "",ZoomInOut=NULL, Zlabels=NULL, Zcol=NULL,
    poslab=c(2,1,3,3), signedCTR = FALSE, relCTR = TRUE,...)
RiskJackplot(x, nbvs = 1:20, mod = NULL, max = NULL, rescaled=TRUE, ...)



an object inheriting from class PTAk, representing a generalised singular value decomposition


logical if TRUE plots the labels given in solution[[mod]]["n"]


vectors of the modes numbers to be plotted


number identifying the Principal Tensor to display on the vertical axe, can be checked using summary.PTAk


as nb1 to be displayed on the horizontal axe, if NULL the horizontal axe will be used as Index (see plot.default)


coefficients to multiply components for all modes (not just the one in mod) for rescaling or changing signs purposes; each element of the list correspond to nb1 and nb2 and are vectors of dimentions the tensor order


logical to display axes labels


a vector of length at least length(mod) used for pch=


a number or a vector of numbers of characters in labels to be used for display


logical to display a screeplot of squared singular values as percent of total variation


logical used when displaying the screeplot with sorted values (TRUE) or the order is given by output listing from summary.PTAk


a maximum number of singular values to display on the screeplot or a vector of ranks


is the number of singular values to be considered as giving the perfect fit, NULL is the max possible in x


boolean to rescale the y axis to 0-100


if not NULL is an integer, scree is TRUE and ordered is TRUE, plots on top of the scree plot a Risk plot with nbvs = 1:RiskJack. It is possible to use directly the function RiskJackplot: the default maximum dimension (argument max) is length(solution[[k]][["d"]]).


default is "", a value "FCA" is to be used only if solution is after an FCA with SVDgen


list used as [[1]] for xlim and [[2]] for ylim in xy-plots instead of max and min range


used as labels instead of x[[mod]]$n, it is a list with the same length as all modes. For example on 3 modes changing the labels of the second mode only will have to set Zlabels=list(NULL,rep("a",length(x[[2]]$n) ), NULL )


list of vectors of colours for Zlabels


integer or vector for 'pos' parameter, position of labels


logical to plot signed-CTR instead of coordinates, see CTR


logical if signedCTR = TRUE use relative CTRs, expected contribution 1 if uniform or equal contributions.


plot arguments can be passed (except xlim, ylim, ylab,pch,xaxt for component plot, and xlab, ylab for screeplot). For example to have normed plot one can use asp=1


Plot components of one or two Principal Tensors, modes are superposed if more than one is asked, or gives a screeplot. As it is using plot.default at some point some added features can be used in the ... part, especially xlab= may be useful when nb2=NULL. Plots are superposed as they correspond to the same Principal Tensor and so this gives insight to interpretation of it, but careful is recommended as only overall interpretation, once the Principal Tensor has been rebuilt mentally (i.e. product of signs ...) to work out oppositions or associations. The risk plot on top of a screeplot is an approximation of the Jacknife estimate of the MSE in the choice of number of dimensions (see Besse et al.(1997)).


This function is used all for FCAk, and CANDPARA, PCAn objjects notheless for this last object other interesting plots known as jointplots have not been implemented.


Didier G. Leibovici


Besse, P Cardot, H and Ferraty, F (1997) Simultaneous non-parametric regressions of unbalanced longitudinal data. Computational Statistics and Data Analysis, 24:255-270.

Leibovici D (2000) Multiway Multidimensional Analysis for Pharmaco-EEG Studies.

See Also



#  see the demo function   source(paste(R.home(),"/ library/PTAk/demo/PTA3.R",sep=""));
# or    source(paste(R.home(),"/ library/PTAk/demo/PTAk.R",sep=""));
 # demo.PTA3()

PTAk documentation built on March 31, 2023, 5:17 p.m.

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