Momocs (version 1.4.1)

MANOVA: Multivariate analysis of (co)variance on Coe objects

Description

Performs multivariate analysis of variance on PCA objects.

Usage

MANOVA(x, fac, test = "Hotelling", retain, drop)
# S3 method for OpnCoe
MANOVA(x, fac, test = "Hotelling", retain, drop)
# S3 method for OutCoe
MANOVA(x, fac, test = "Hotelling", retain, drop)
# S3 method for PCA
MANOVA(x, fac, test = "Hotelling", retain = 0.99, drop)

Value

a list of matrices of (x,y) coordinates.

Arguments

x

a Coe object

fac

a name of a colum in the $fac slot, or its id, or a formula

test

a test for manova ('Hotelling' by default)

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

Details

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.

See Also

Other multivariate: CLUST(), KMEANS(), KMEDOIDS(), LDA(), MANOVA_PW(), MDS(), MSHAPES(), NMDS(), PCA(), classification_metrics()

Examples

# 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")