| MANOVA | R Documentation | 
Performs multivariate analysis of variance on PCA objects.
MANOVA(x, fac, test = "Hotelling", retain, drop)
## S3 method for class 'OpnCoe'
MANOVA(x, fac, test = "Hotelling", retain, drop)
## S3 method for class 'OutCoe'
MANOVA(x, fac, test = "Hotelling", retain, drop)
## S3 method for class 'PCA'
MANOVA(x, fac, test = "Hotelling", retain = 0.99, drop)
x | 
 a Coe object  | 
fac | 
 a name of a colum in the   | 
test | 
 a test for manova (  | 
retain | 
 how many harmonics (or polynomials) to retain, for PCA the highest number of PC axis to retain, or the proportion of the variance to capture.  | 
drop | 
 how many harmonics (or polynomials) to drop  | 
Performs a MANOVA/MANCOVA on PC scores. Just a wrapper around manova. See examples for multifactorial manova and summary.manova for more details and examples.
a list of matrices of (x,y) coordinates.
Needs a review and should be considered as experimental.
Silent message and progress bars (if any) with options("verbose"=FALSE).
Other multivariate: 
CLUST(),
KMEANS(),
KMEDOIDS(),
LDA(),
MANOVA_PW(),
MDS(),
MSHAPES(),
NMDS(),
PCA(),
classification_metrics()
# MANOVA
bot.p <- PCA(efourier(bot, 12))
MANOVA(bot.p, 'type')
op <- PCA(npoly(olea, 5))
MANOVA(op, 'domes')
 m <- manova(op$x[, 1:5] ~  op$fac$domes * op$fac$var)
 summary(m)
 summary.aov(m)
 # MANCOVA example
 # we create a numeric variable, based on centroid size
 bot %<>% mutate(cs=coo_centsize(.))
 # same pipe
 bot %>% efourier %>% PCA %>% MANOVA("cs")
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