s.multinom {ade4} | R Documentation |
The main purpose of this function is to draw categories using scores and profiles by their gravity center. Confidence intervals of the average position (issued from a multinomial distribution) can be superimposed.
s.multinom(dfxy, dfrowprof, translate = FALSE, xax = 1, yax = 2, labelcat = row.names(dfxy), clabelcat = 1, cpointcat = if (clabelcat == 0) 2 else 0, labelrowprof = row.names(dfrowprof), clabelrowprof = 0.75, cpointrowprof = if (clabelrowprof == 0) 2 else 0, pchrowprof = 20, coulrowprof = grey(0.8), proba = 0.95, n.sample = apply(dfrowprof, 1, sum), axesell = TRUE, ...)
dfxy |
|
dfrowprof |
|
translate |
a logical value indicating whether the plot should be translated(TRUE) or not. The origin becomes the gravity center weighted by profiles. |
xax |
the column number of |
yax |
the column number of |
labelcat |
a vector of strings of characters for the labels of categories |
clabelcat |
an integer specifying the character size for the labels of categories,
used with |
cpointcat |
an integer specifying the character size for the points showing the categories,
used with |
labelrowprof |
a vector of strings of characters for the labels of profiles (rows of |
clabelrowprof |
an integer specifying the character size for the labels of profiles used with par("cex")*clabelrowprof |
cpointrowprof |
an integer specifying the character size for the points representative of the profiles used with par("cex")*cpointrowprof |
pchrowprof |
either an integer specifying a symbol or a single character to be used for the profile labels |
coulrowprof |
a vector of colors used for ellipses, possibly recycled |
proba |
a value lying between 0.500 and 0.999 to draw a confidence interval |
n.sample |
a vector containing the sample size, possibly recycled. Used |
axesell |
a logical value indicating whether the ellipse axes should be drawn |
... |
further arguments passed from the |
Returns in a hidden way a list of three components :
tra |
a vector with two values giving the done original translation. |
ell |
a matrix, with 5 columns and for rows the number of profiles, giving the means,
the variances and the covariance of the profile for the used
numerical codes (column of |
call |
the matched call |
Daniel Chessel
par(mfrow = c(2,2)) par(mar = c(0.1,0.1,0.1,0.1)) proba <- matrix(c(0.49,0.47,0.04,0.4,0.3,0.3,0.05,0.05,0.9,0.05,0.7,0.25), ncol = 3, byrow = TRUE) proba.df <- as.data.frame (proba) names(proba.df) <- c("A","B","C") ; row.names(proba.df) <- c("P1","P2","P3","P4") w.proba <- triangle.plot(proba.df, clab = 2, show = FALSE) box() w.tri = data.frame(x = c(-sqrt(1/2),sqrt(1/2),0), y = c(-1/sqrt(6),-1/sqrt(6),2/sqrt(6))) L3 <- c("A","B","C") row.names(w.tri) <- L3 s.multinom(w.tri, proba.df, n.sample = 0, coulrowprof = "black", clabelrowprof = 1.5) s.multinom(w.tri, proba.df, n.sample = 30, coul = palette()[5]) s.multinom(w.tri, proba.df, n.sample = 60, coul = palette()[6], add.p = TRUE) s.multinom(w.tri, proba.df, n.sample = 120, coul = grey(0.8), add.p = TRUE) print(s.multinom(w.tri, proba.df[-3,], n.sample = 0, translate = TRUE)$tra)