Correlation circle of multivariate analyses
Displays a correlation circle of a multivariate analysis.
MVA.corplot(x, xax = 1, yax = 2, thresh = 0, fac = NULL, set = c(12, 1, 2), space = 1, xlab = NULL, ylab = NULL, main = NULL, circle = TRUE, intcircle = 0.5, points = TRUE, ident = TRUE, arrows = TRUE, labels = NULL, main.pos = c("bottomleft", "topleft", "bottomright", "topright"), main.cex = 1.3, legend = FALSE, legend.pos = c("topleft", "topright", "bottomleft", "bottomright"), legend.title = NULL, legend.lab = NULL, pch = 16, cex = 1, col = 1, lwd = 1, drawintaxes = TRUE, add = FALSE, add.const = 1, keepmar = FALSE)
x: a multivariate analysis (see Details).xax: the horizontal axis.yax: the vertical axis. This can be set to NULL for a one-dimensional graph, which is a dotchart.thresh: threshold (in absolute value of the correlation coefficient) of variables to be plotted.fac: an optional factor defining groups of variables.set: variables to be displayed, when several sets are available (see Details). 12 (default) for both sets, 1 for X or constraints, 2 for Y or constrained variables.space: variables to be displayed, when several spaces are available (see Details). space is the number of the space to be plotted.xlab: legend of the horizontal axis. If NULL (default), automatic labels are used depending on the multivariate analysis.ylab: only used for two-dimensional graphs. Legend of the vertical axis. If NULL (default), automatic labels are used depending on the multivariate analysis.main: optional title of the graph.circle: only used for two-dimensional graphs. Logical indicating if the circle of radius 1 should be plotted.intcircle: only used for two-dimensional graphs. Vector of one or several values indicating radii of circles to be plotted inside the main circle. Can be set to NULL.points: only used for two-dimensional graphs. If FALSE, arrows or points (see arrows) are replaced with their corresponding label (defined by labels).ident: only used for two-dimensional graphs when points=TRUE. A logical indicating if variable names should be displayed.arrows: only used if points=TRUE. Logical indicating if arrows should be plotted. If FALSE, points are displayed at the extremity of the arrows.labels: names of the variables. If NULL (default), labels correspond to variable names found in the data used in the multivariate analysis. For two-dimensional graphs, only used if ident=TRUE.main.pos: position of the title, if main is not NULL. Default to "bottomleft".main.cex: size of the title, if main is not NULL.legend: only used for two-dimensional graphs. Logical indicating if a legend should be added to the graph.legend.pos: position of the legend, if legend is TRUE. Default to "topleft".legend.title: optional title of the legend, if legend is TRUE.legend.lab: legend labels, if legend is TRUE. If NULL, levels of the factor defined by fac are used.pch: symbol(s) used for points, when points are displayed (see arrows). If fac is not NULL, can be a vector of length one or a vector giving one value per group. Otherwise a vector of any length can be defined, which is recycled if necessary.cex: size of the points and/or of the variable names. For two-dimensional graphs: if fac is not NULL, can be a vector of length one or a vector giving one value per group; otherwise a vector of any length can be defined, which is recycled if necessary. For dotcharts, gives the size used for points and all labels (see dotchart).col: color(s) used for points and/or variable names. If fac is not NULL, can be a vector of length one or a vector giving one value per group. Otherwise a vector of any length can be defined, which is recycled if necessary (not available for density histograms, see dhist).lwd: only used if arrows are displayed. Width of arrows. If fac is not NULL, can be a vector of length one or a vector giving one value per group. Otherwise a vector of any length can be defined, which is recycled if necessary.drawintaxes: logical indicating if internal axes should be drawn.add: only used for two-dimensional graphs. Logical indicating if the correlation circle should be added to an existing graph.add.const: only used for two-dimensional graphs and if add is TRUE. Constant by which correlations are multiplied to fit onto the original graph.keepmar: only used for two-dimensional graphs. Logical indicating if margins defined by MVA.corplot should be kept after plotting (necessary in some cases when add=TRUE).This function should not be use directly. Prefer the general MVA.plot, to which all arguments can be passed.
Many multivariate analyses are supported, from various packages:
PCA: dudi.pca, rda.
sPCA: spca.
IPCA: ipca.
sIPCA: sipca.
LDA: lda, discrimin.
PLS-DA (PLS2 on a dummy-coded factor): plsda. X space only.
sPLS-DA (sPLS2 on a dummy-coded factor): splsda. X space only.
CPPLS: mvr. Set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set. X space only.
PLSR: mvr, pls, plsR (plsRglm package). Set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set. X space only.
sPLSR: pls. Set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set. X space only.
PLS-GLR: plsRglm (plsRglm package). Set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set. Correlations are computed with Y on the link scale.
PCR: mvr. Set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
CDA: discrimin, discrimin.coa.
NSCOA: dudi.nsc. For NSCOA there is no real correlation, but the classical representation of columns is arrows. This is why MVA.corplot was made able to deal with this analysis.
CCA: cca, pcaiv. Constraints (only quantitative constraints are extracted) in constrained space only.
Mix analysis: dudi.mix, dudi.hillsmith. Only quantitative variables are displayed.
RDA (or PCAIV): pcaiv, pcaivortho, rda. With rda, space 1 is constrained space, space 2 is unconstrained space. Only constrained space is available with pcaiv, the opposite for pcaivortho. Set 1 is constraints (only quantitative constraints are extracted), set 2 is dependent variables (only set 2 is available for pcaivortho). If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
db-RDA: capscale, dbrda. Constraints (only quantitative constraints are extracted) in constrained space only.
CCorA: CCorA, rcc. Space 1 is X, space 2 is Y. With rcc a third space is available, in which coordinates are means of X and Y coordinates. In this third space, set 1 is X, set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
rCCorA: rcc. Space 1 is X, space 2 is Y, space 3 is a "common" space in which coordinates are means of X and Y coordinates. In space 3, set 1 is X and set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
CIA: coinertia. Space 1 is X, space 2 is Y, space 3 is a "common" space where X and Y scores are normed. In space 3, set 1 is X and set 2 is Y. If set=12 in space 3 (default), fac is not available and pch,cex, col, lws can be defined differently for each set.
PCIA: procuste. Set 1 is X, set 2 is Y.
2B-PLS: pls. Space 1 is X, space 2 is Y, space 3 is a "common" space in which coordinates are means of X and Y coordinates. In space 3, set 1 is X and set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
2B-sPLS: pls. Space 1 is X, space 2 is Y, space 3 is a "common" space in which coordinates are means of X and Y coordinates. In space 3, set 1 is X and set 2 is Y. If set=12 (default), fac is not available and pch,cex, col, lwd can be defined differently for each set.
rGCCA: wrapper.rgcca. Space can be 1 to n, the number of blocks (i.e. datasets).
sGCCA: wrapper.sgcca. Space can be 1 to n, the number of blocks (i.e. datasets).
DIABLO: block.plsda, block.splsda. Space can be 1 to n, the number of blocks (i.e. datasets).
Maxime HERVE maxime.herve@univ-rennes1.fr
require(ade4) data(olympic) PCA <- dudi.pca(olympic$tab,scannf=FALSE) MVA.plot(PCA,"corr")
Useful links