A table of Qualitative Variables
ours.Rd
The ours
(bears) data frame has 38 rows, areas of the "Inventaire National Forestier", and 10 columns.
Usage
data(ours)
Format
This data frame contains the following columns:
altit: importance of the altitudinal area inhabited by bears, a factor with levels:
1
less than 50% of the area between 800 and 2000 meters2
between 50 and 70%3
more than 70%
deniv: importance of the average variation in level by square of 50 km2, a factor with levels:
1
less than 700m2
between 700 and 900 m3
more than 900 m
cloiso: partitioning of the massif, a factor with levels:
1
a great valley or a ridge isolates at least a quarter of the massif2
less than a quarter of the massif is isolated3
the massif has no split
domain: importance of the national forests on contact with the massif, a factor with levels:
1
less than 400 km22
between 400 and 1000 km23
more than 1000 km2
boise: rate of afforestation, a factor with levels:
1
less than 30%2
between 30 and 50%3
more than 50%
hetra: importance of plantations and mixed forests, a factor with levels:
1
less than 5%2
between 5 and 10%3
more than 10% of the massif
favor: importance of favorable forests, plantations, mixed forests, fir plantations, a factor with levels:
1
less than 5%2
between 5 and 10%3
more than 10% of the massif
inexp: importance of unworked forests, a factor with levels:
1
less than 4%2
between 4 and 8%3
more than 8% of the total area
citat: presence of the bear before its disappearance, a factor with levels:
1
no quotation since 18402
1 to 3 quotations before 1900 and none after3
4 quotations before 1900 and none after4
at least 4 quotations before 1900 and at least 1 quotation between 1900 and 1940
depart: district, a factor with levels:
AHP
Alpes-de-Haute-ProvenceAM
Alpes-MaritimesD
DrômeHP
Hautes-AlpesHS
Haute-SavoieI
IsèreS
Savoie
Source
Erome, G. (1989) L'ours brun dans les Alpes françaises. Historique de sa disparition. Centre Ornithologique Rhône-Alpes, Villeurbanne. 120 p.
Examples
data(ours)
if(adegraphicsLoaded()) {
s1d.boxplot(dudi.acm(ours, scan = FALSE)$l1[, 1], ours)
} else {
boxplot(dudi.acm(ours, scan = FALSE))
}