ours {ade4} | R Documentation |
The ours
(bears) data frame has 38 rows, areas of the "Inventaire National Forestier", and 10 columns.
data(ours)
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 meters
2
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 700m
2
between 700 and 900 m
3
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 massif
2
less than a quarter of the massif is isolated
3
the massif has no split
domain: importance of the national forests on contact with the massif, a factor with levels:
1
less than 400 km2
2
between 400 and 1000 km2
3
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 1840
2
1 to 3 quotations before 1900 and none after
3
4 quotations before 1900 and none after
4
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-Provence
AM
Alpes-Maritimes
D
Drôme
HP
Hautes-Alpes
HS
Haute-Savoie
I
Isère
S
Savoie
Erome, G. (1989) L'ours brun dans les Alpes françaises. Historique de sa disparition. Centre Ornithologique Rhône-Alpes, Villeurbanne. 120 p.
data(ours) if(adegraphicsLoaded()) { s1d.boxplot(dudi.acm(ours, scan = FALSE)$l1[, 1], ours) } else { boxplot(dudi.acm(ours, scan = FALSE)) }