ade4ade4## S3 method for class 'foucart':
kplot(object, xax = 1, yax = 2, which.tab = 1:length(object$blo), pos = -1,
storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'mcoa':
kplot(object, xax = 1, yax = 2, which.tab = 1:nrow(object$cov2),
option = c("points", "axis", "columns"), pos = -1, storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'mfa':
kplot(object, xax = 1, yax = 2, which.tab = 1:length(object$blo), traject = FALSE,
permute = FALSE, pos = -1, storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'mbpcaiv':
kplot(object, xax = 1, yax = 2, which.tab =
1:length(object$blo), pos = -1, storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'pta':
kplot(object, xax = 1, yax = 2, which.tab = 1:nrow(object$RV), which.graph = 1:4,
pos = -1, storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'sepan':
kplot(object, xax = 1, yax = 2, which.tab = 1:length(object$blo), permute = FALSE,
traject = FALSE, posieig = "bottomleft", pos = -1, storeData = TRUE, plot = TRUE, ...)
kplotsepan.coa(object, xax = 1, yax = 2, which.tab = 1:length(object$blo),
permute = FALSE, posieig = "bottomleft", pos = -1, storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'statis':
kplot(object, xax = 1, yax = 2, which.tab = 1:length(object$tab.names), traject = FALSE,
arrow = TRUE, class = NULL, pos = -1, storeData = TRUE, plot = TRUE, ...)## S3 method for class 'acm':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'betcoi':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'betdpcoa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'betwitdpcoa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'betrlq':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'between':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'coinertia':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'discrimin':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'dpcoa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'fca':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'foucart':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE,
plot = TRUE, \dots)
## S3 method for class 'krandboot':
plot(x, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'krandxval':
plot(x, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'mcoa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'mfa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE,
plot = TRUE, \dots)
## S3 method for class 'multiblock':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'multispati':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'niche':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'pcaiv':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'pta':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'procuste':
plot(x, xax = 1, yax = 2, pos = -1, storeData =
TRUE, plot = TRUE, \dots)
## S3 method for class 'randboot':
plot(x, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'randxval':
plot(x, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'rlq':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'sepan':
plot(x, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'statis':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'witcoi':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'witdpcoa':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'within':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'witrlq':
plot(x, xax = 1, yax = 2, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'dudi':
scatter(x, xax = 1, yax = 2, permute = FALSE, posieig = "topleft", prop = FALSE,
density.plot = ifelse(permute, ncol(x$tab) > 1000, nrow(x$tab) > 1000), plot = TRUE,
storeData = TRUE, pos = -1, ...)
## S3 method for class 'coa':
scatter(x, xax = 1, yax = 2, method = 1:3, posieig = "topleft", pos = -1,
storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'pco':
scatter(x, xax = 1, yax = 2, posieig = "topleft", pos = -1, storeData = TRUE,
plot = TRUE, \dots)
## S3 method for class 'nipals':
scatter(x, xax = 1, yax = 2, posieig = "topleft", pos = -1, storeData = TRUE,
plot = TRUE, \dots)
## S3 method for class 'acm':
score(x, xax = 1, which.var = NULL, type = c("points", "boxplot"), pos = -1,
storeData = TRUE, plot = TRUE, ...)
## S3 method for class 'mix':
score(x, xax = 1, which.var = NULL, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'pca':
score(x, xax = 1, which.var = NULL, pos = -1, storeData = TRUE, plot = TRUE, \dots)
## S3 method for class 'dudi':
screeplot(x, col.kept = "grey", col = "white", pos = -1, plot = TRUE, \dots)
## S3 method for class 'dudi':
biplot(x, pos = -1, plot = TRUE, \dots)
x is(are) plotted on the x-axisx is(are) plotted on the y-axiskplot.*) containing the numbers of the tables used for the analysiskplot.mfa) indicating the drawing option:
points plot of the projected scattergram onto the co-inertia axes,
axis projections of inertia axes onto the co-inertia axes,
kplot.pta) indicating the drawing option.
For each table of which.tab, are drawn:
1 the projections of the principal axes,
2 the projections of the rokplot.sepan, kplotsepan.coa and scatter.dudi).
If FALSE, the rows are plotted by points or density surface and the columns by arrows. If TRUE, it is the oppositekplot.sepan and kplot.statis)
indicating whether the trajectories between rows should be drawn in a natural ordernpc from 0 to 1)
or none value indicating the position of the eigenvalues bar plot (used in kplot.sepan, kplotsepan.coakplot.statis) indicating whether the column factorial diagrams should be plottedkplot.statis)scatter.dudi) indicating if the size of the arrows' labels is proportional to the analysis score.scatter.dudi)indicating if the points are displayed as density surface (using s.density).scatter.coa) indicating the drawing option. Are drawn:
1 rows and columns with the coordinates of lambda variance,
2 rows variance 1 and columns by averaging,
score.*)score.acm) indicating if points (points) or boxplot (boxplot) are used to represent levels of factorsscreeplot.dudi)screeplot.dudi)FALSE, only the names of the data
arguments are storedstoreData is
FALSEadegpar and trellis.par.get)ADEg or an ADEgS object.
The result is displayed if plot is TRUE.ade4 website: cat("To run the example on 'topic'
")
cat("Type in your R console: example(topic, package = 'ade4')
")Run the code above in your browser using DataLab