table.cont {ade4} | R Documentation |
Plot of Contingency Tables
Description
presents a graph for viewing contingency tables.
Usage
table.cont(df, x = 1:ncol(df), y = 1:nrow(df),
row.labels = row.names(df), col.labels = names(df),
clabel.row = 1, clabel.col = 1, abmean.x = FALSE, abline.x = FALSE,
abmean.y = FALSE, abline.y = FALSE, csize = 1, clegend = 0, grid = TRUE)
Arguments
df |
a data frame with only positive or null values |
x |
a vector of values to position the columns |
y |
a vector of values to position the rows |
row.labels |
a character vector for the row labels |
col.labels |
a character vetor for the column labels |
clabel.row |
a character size for the row labels |
clabel.col |
a character size for the column labels |
abmean.x |
a logical value indicating whether the column conditional means should be drawn |
abline.x |
a logical value indicating whether the regression line of y onto x should be plotted |
abmean.y |
a logical value indicating whether the row conditional means should be drawn |
abline.y |
a logical value indicating whether the regression line of x onto y should be plotted |
csize |
a coefficient for the square size of the values |
clegend |
if not NULL, a character size for the legend used with |
grid |
a logical value indicating whether a grid in the background of the plot should be drawn |
Author(s)
Daniel Chessel
Examples
data(chats)
chatsw <- data.frame(t(chats))
chatscoa <- dudi.coa(chatsw, scann = FALSE)
par(mfrow = c(2,2))
table.cont(chatsw, abmean.x = TRUE, csi = 2, abline.x = TRUE,
clabel.r = 1.5, clabel.c = 1.5)
table.cont(chatsw, abmean.y = TRUE, csi = 2, abline.y = TRUE,
clabel.r = 1.5, clabel.c = 1.5)
table.cont(chatsw, x = chatscoa$c1[,1], y = chatscoa$l1[,1],
abmean.x = TRUE, csi = 2, abline.x = TRUE, clabel.r = 1.5, clabel.c = 1.5)
table.cont(chatsw, x = chatscoa$c1[,1], y = chatscoa$l1[,1],
abmean.y = TRUE, csi = 2, abline.y = TRUE, clabel.r = 1.5, clabel.c = 1.5)
par(mfrow = c(1,1))
## Not run:
data(rpjdl)
w <- data.frame(t(rpjdl$fau))
wcoa <- dudi.coa(w, scann = FALSE)
table.cont(w, abmean.y = TRUE, x = wcoa$c1[,1], y = rank(wcoa$l1[,1]),
csi = 0.2, clabel.c = 0, row.labels = rpjdl$lalab, clabel.r = 0.75)
## End(Not run)