mfa {ade4} | R Documentation |
performs a multiple factorial analysis,
using an object of class ktab
.
mfa(X, option = c("lambda1", "inertia", "uniform", "internal"), scannf = TRUE, nf = 3) plot.mfa (x, xax = 1, yax = 2, option.plot = 1:4, ...) print.mfa (x, ...) summary.mfa (object, ...)
X |
K-tables, an object of class ktab |
option |
a string of characters for the weighting of arrays options :
lambda1 inertia uniform internal X$tabw |
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 |
x, object |
an object of class 'mfa' |
xax, yax |
the numbers of the x-axis and the y-axis |
option.plot |
an integer between 1 and 4, otherwise the 4 components of the plot are displayed |
... |
further arguments passed to or from other methods |
Returns a list including :
tab |
a data frame with the modified array |
rank |
a vector of ranks for the analyses |
eig |
a numeric vector with the all eigenvalues |
li |
a data frame with the coordinates of rows |
TL |
a data frame with the factors associated to the rows (indicators of table) |
co |
a data frame with the coordinates of columns |
TC |
a data frame with the factors associated to the columns (indicators of table) |
blo |
a vector indicating the number of variables for each table |
lisup |
a data frame with the projections of normalized scores of rows for each table |
cg |
a data frame with the gravity center for the lisup |
link |
a data frame containing the projected inertia and the links between the arrays and the reference array |
corli |
a data frame giving the correlations between the $lisup and the $li |
Daniel Chessel chessel@biomserv.univ-lyon1.fr
Anne B Dufour dufour@biomserv.univ-lyon1.fr
Escofier, B. and Pagès, J. (1994) Multiple factor analysis (AFMULT package), Computational Statistics and Data Analysis, 18, 121–140.
data(friday87) w1 <- data.frame(scale(friday87$fau, scal = FALSE)) w2 <- ktab.data.frame(w1, friday87$fau.blo, tabnames = friday87$tab.names) mfa1 <- mfa(w2, scann = FALSE) mfa1 plot(mfa1) data(escopage) w <- data.frame(scale(escopage$tab)) w <- ktab.data.frame(w, escopage$blo, tabnames = escopage$tab.names) plot(mfa(w, scann = FALSE))