witwit.coa {ade4} | R Documentation |
witwit.coa
performs an Internal Correspondence Analysis.
witwitsepan
gives the computation and the barplot of the eigenvalues
for each separated analysis in an Internal Correspondence Analysis.
witwit.coa(dudi, row.blocks, col.blocks, scannf = TRUE, nf = 2) summary.witwit(object, ...) witwitsepan(ww, mfrow = NULL, csub = 2, plot = TRUE)
dudi |
an object of class coa |
row.blocks |
a numeric vector indicating the row numbers for each block of rows |
col.blocks |
a numeric vector indicating the column numbers for each block of columns |
scannf |
a logical value indicating whether the eigenvalues bar plot should be displayed |
nf |
if scannf FALSE, an integer indicating the number of kept axes |
object |
an object of class witwit |
... |
further arguments passed to or from other methods |
ww |
an object of class witwit |
mfrow |
|
csub |
|
plot |
{if FALSE, numeric results are returned}
returns a list of class witwit
, coa
and dudi
(see as.dudi) containing
rbvar |
a data frame with the within variances of the rows of the factorial coordinates |
lbw |
a data frame with the marginal weighting of the row classes |
cvar |
a data frame with the within variances of the columns of the factorial coordinates |
cbw |
a data frame with the marginal weighting of the column classes |
Daniel Chessel chessel@biomserv.univ-lyon1.fr Anne B Dufour dufour@biomserv.univ-lyon1.fr
Cazes, P., Chessel, D. and Dolédec, S. (1988) L'analyse des correspondances internes d'un tableau partitionné : son usage en hydrobiologie. Revue de Statistique Appliquée, 36, 39–54.
data(ardeche) coa1 <- dudi.coa(ardeche$tab, scann = FALSE, nf = 4) ww <- witwit.coa(coa1, ardeche$row.blocks, ardeche$col.blocks, scann = FALSE) ww s.class(ww$co, ardeche$sta.fac, clab = 1.5, cell = 0, axesell = FALSE) s.label(ww$co, add.p = TRUE, clab = 0.75) summary(ww) witwitsepan(ww, c(4,6))