# MANOVA: Multivariate analysis of (co)variance on Coe objects In Momocs: Morphometrics using R

## Description

Performs multivariate analysis of variance on PCA objects.

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10``` ```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) ```

## 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.

## Value

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

## Note

Needs a review and should be considered as experimental. Silent message and progress bars (if any) with `options("verbose"=FALSE)`.

Other multivariate: `CLUST`, `KMEANS`, `LDA`, `MANOVA_PW`, `PCA`, `classification_metrics`, `mshapes`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# 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") ```