fruits {ade4} | R Documentation |
28 batches of fruits -two types- are judged by two different ways.
They are classified in order of preference, without ex aequo, by 16 individuals.
15 quantitative variables described the batches of fruits.
data(fruits)
fruits
is a list of 3 components:
is a vector returning the type of the 28 batches of fruits (peaches or nectarines).
is a data frame of 28 rows and 16 columns (judges).
is a data frame of 28 rows and 16 measures (average of 2 judgements).
fruits$var
is a data frame of 15 variables:
taches: quantity of cork blemishes (0=absent - maximum 5)
stries: quantity of stria (1/none - maximum 4)
abmucr: abundance of mucron (1/absent - 4)
irform: shape irregularity (0/none - 3)
allong: length of the fruit (1/round fruit - 4)
suroug: percentage of the red surface (minimum 40% - maximum 90%)
homlot: homogeneity of the intra-batch coloring (1/strong - 4)
homfru: homogeneity of the intra-fruit coloring (1/strong - 4)
pubesc: pubescence (0/none - 4)
verrou: intensity of green in red area (1/none - 4)
foncee: intensity of dark area (0/pink - 4)
comucr: intensity of the mucron color (1=no contrast - 4/dark)
impres: kind of impression (1/watched - 4/pointillé)
coldom: intensity of the predominating color (0/clear - 4)
calibr: grade (1/<90g - 5/>200g)
Kervella, J. (1991) Analyse de l'attrait d'un produit : exemple d'une comparaison de lots de pêches. Agro-Industrie et méthodes statistiques. Compte-rendu des secondes journées européennes. Nantes 13-14 juin 1991. Association pour la Statistique et ses Utilisations, Paris, 313–325.
data(fruits) pcajug <- dudi.pca(fruits$jug, scann = FALSE) pcavar <- dudi.pca(fruits$var, scann = FALSE) if(adegraphicsLoaded()) { g1 <- s.corcircle(pcajug$co, plot = FALSE) g2 <- s.class(pcajug$li, fac = fruits$type, plot = FALSE) g3 <- s.corcircle(pcavar$co, plot = FALSE) g4 <- s.class(pcavar$li, fac = fruits$type, plot = FALSE) G1 <- ADEgS(list(g1, g2, g3, g4), layout = c(2, 2)) G2 <- plot(coinertia(pcajug, pcavar, scan = FALSE)) } else { par(mfrow = c(2,2)) s.corcircle(pcajug$co) s.class(pcajug$li, fac = fruits$type) s.corcircle(pcavar$co) s.class(pcavar$li, fac = fruits$type) par(mfrow = c(1,1)) plot(coinertia(pcajug, pcavar, scan = FALSE)) }