escouf | R Documentation |
Calculate equivalent vectors sensu Escoufier, that is, most significant variables from a multivariate data frame according to a principal component analysis (variables that are most correlated with the principal axes). This method is useful mainly for physical or chemical data where simply summarizing them with a PCA does not always gives easily interpretable principal axes.
escouf(x, level=1, verbose=TRUE)
## S3 method for class 'escouf'
print(x, ...)
## S3 method for class 'escouf'
summary(object, ...)
## S3 method for class 'summary.escouf'
print(x, ...)
## S3 method for class 'escouf'
plot(x, level=x$level, lhorz=TRUE, lvert=TRUE, lvars=TRUE,
lcol=2, llty=2, diff=TRUE, dlab="RV' (units not shown)", dcol=4,
dlty=par("lty"), dpos=0.8, type="s", xlab="variables", ylab="RV",
main=paste("Escoufier's equivalent vectors for:",x$data), ...)
## S3 method for class 'escouf'
lines(x, level=x$level, lhorz=TRUE, lvert=TRUE, lvars=TRUE,
col=2, lty=2, ...)
## S3 method for class 'escouf'
identify(x, lhorz=TRUE, lvert=TRUE, lvars=TRUE, col=2,
lty=2, ...)
## S3 method for class 'escouf'
extract(e, n, level=e$level, ...)
x |
For |
level |
The level of correlation at which to stop calculation. By default |
verbose |
Print calculation steps. This allows to control the percentage of calculation already achieved when computation takes a long time (that is, with many variables to sort) |
object |
An 'escouf' object returned by |
e |
An 'escouf' object returned by |
lhorz |
If |
lvert |
If |
lvars |
If |
lcol |
The color to use to draw the lines ( |
llty |
The style used to draw the lines ( |
diff |
If |
dlab |
The label to use for the RV' curve. By default: |
dcol |
The color to use for the RV' curve (by default, color 4 is used) |
type |
The type of graph to plot |
xlab |
the label of the x-axis |
ylab |
the label of the y-axis |
main |
the main title of the graph |
dlty |
The style for the RV' curve |
col |
The color to use to draw the lines ( |
lty |
The style used to draw the lines ( |
dpos |
The relative horizontal position of the label for the RV' curve. The default value of 0.8 means that the label is placed at 80% of the horizontal axis.Vertical position of the label is automatically determined |
n |
The number of variables to extract. If a value is given, it has the priority on |
... |
additional parameters |
An object of type 'escouf' is returned. It has methods print()
, summary()
, plot()
, lines()
, identify()
, extract()
.
Since a large number of iterations is done, this function is slow with a large number of variables (more than 25-30)!
Frédéric Ibanez (ibanez@obs-vlfr.fr), Philippe Grosjean (phgrosjean@sciviews.org), Benjamin Planque (Benjamin.Planque@ifremer.fr), Jean-Marc Fromentin (Jean.Marc.Fromentin@ifremer.fr)
Cambon, J., 1974. Vecteur équivalent à un autre au sens des composantes principales. Application hydrologique. DEA de Mathématiques Appliquées, Université de Montpellier.
Escoufier, Y., 1970. Echantillonnage dans une population de variables aléatoires réelles. Pub. Inst. Stat. Univ. Paris, 19:1-47.
Jabaud, A., 1996. Cadre climatique et hydrobiologique du lac Léman. DEA d'Océanologie Biologique Paris.
abund
data(marbio)
marbio.esc <- escouf(marbio)
summary(marbio.esc)
plot(marbio.esc)
# The x-axis has short labels. For more info., enter:
marbio.esc$vr
# Define a level at which to extract most significant variables
marbio.esc$level <- 0.90
# Show it on the graph
lines(marbio.esc)
# This can also be done interactively on the plot using:
# marbio.esc$level <- identify(marbio.esc)
# Finally, extract most significant variables
marbio2 <- extract(marbio.esc)
names(marbio2)
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