Description Usage Arguments Value Author(s) References Examples
Identifies outliers based on the nearest neighbour criterion. It starts by computing a matrix of distances (correlation, r, used as distance, dr=(1-r)/2). Variables with nearest neighbour distance larger than parameter thresh are considered outliers.
1 2 3 4 5 6 7 8 9 |
veg |
This is a vegetation data frame, releves are rows, species columns |
thresh |
Threshold nearest neighbour distance for outliers |
y |
Transformation of species scores: x'= x exp(y) |
x |
An object of class "outlier" |
... |
Parameter out.seq, the plotting interval |
An object of class "oulier" with at least the following items:
threshold |
Threshold nearest neighbour distance for considering outliers |
y |
Transformation of species scores: x'= x exp(y) |
rel.names |
All row names |
neigh.names |
Names of the corresponding nearest neighbours |
neigh.dist |
Distance to the nearest neighbour |
olddim |
Dimensions of data frame veg |
newdim |
Dimensions of data frame with outliers erased |
new.data |
Vegetation data frame without outliers |
pco.points |
The pco ordination scores use for plotting |
Otto Wildi
Wildi, O. 2017. Data Analysis in Vegetation Ecology. 3rd ed. CABI, Oxfordshire, Boston.
1 2 3 4 | |
Loading required package: labdsv
Loading required package: mgcv
Loading required package: nlme
This is mgcv 1.8-20. For overview type 'help("mgcv-package")'.
Loading required package: MASS
Loading required package: cluster
Attaching package: 'labdsv'
The following object is masked from 'package:stats':
density
Loading required package: vegan
Loading required package: permute
Loading required package: lattice
This is vegan 2.4-4
Call:
outlier.default(veg = nveg, thresh = 0.2, y = 0.5)
Threshold value: 0.2
Original number of releves, species: 11 21
Remaining number of releves, species: 10 21
$threshold
[1] 0.2
$y
[1] 0.5
$rel.names
[1] "2" "4" "6" "9" "10" "18" "25" "27" "39" "49" "50"
$neigh.names
[1] "6" "10" "2" "39" "4" "9" "49" "4" "9" "2" "9"
$neigh.dist
2 4 6 9 10 18 25
0.11050856 0.14115809 0.11050856 0.07310725 0.14115809 0.11175884 0.15612706
27 39 49 50
0.17173665 0.07310725 0.12625106 0.23387803
$olddim
[1] 11 21
$newdim
[1] 10 21
$new.data
Fagus.silvatica Quercus.petraea Acer.pseudoplatanus Fraxinus.excelsior
2 4 2 0 0
4 1 0 2 4
6 5 3 0 0
9 5 2 2 1
10 3 0 3 4
18 6 1 1 1
25 5 4 0 0
27 2 1 5 3
39 6 1 1 0
49 3 5 0 0
Lonicera.xylosteum Sambucus.racemosa Sambucus.nigra Vaccinium.myrtillus
2 1 3 0 3
4 2 0 1 0
6 0 2 0 2
9 0 0 0 0
10 1 0 3 0
18 0 0 1 0
25 1 0 0 0
27 2 0 2 0
39 1 0 0 0
49 0 1 0 1
Carex.silvatica Oxalis.acetosella Viola.silvestris Luzula.nemorosa
2 1 1 1 3
4 1 2 1 0
6 2 1 1 1
9 1 2 2 0
10 0 3 0 0
18 3 2 0 0
25 0 1 0 2
27 3 0 1 0
39 1 4 1 0
49 1 0 1 3
Veronica.officinalis Galium.odoratum Lamium.galeobdolon Primula.elatior
2 2 1 1 0
4 0 1 3 1
6 2 0 1 0
9 0 2 1 0
10 0 1 2 3
18 0 3 0 0
25 1 1 0 0
27 0 2 3 3
39 0 1 1 0
49 1 1 0 0
Allium.ursinum Arum.maculatum Ranunculus.ficaria Eurhynchium.striatum
2 0 0 0 2
4 5 2 2 1
6 0 0 0 0
9 0 0 0 2
10 3 0 3 0
18 0 0 0 1
25 0 0 0 1
27 1 1 5 1
39 0 0 0 1
49 0 0 0 1
Polytrichum.formosum
2 1
4 0
6 2
9 0
10 0
18 0
25 1
27 0
39 0
49 4
$pco.points
[,1] [,2]
2 0.395765653 -0.05447323
4 -0.458798003 -0.05379030
6 0.342524909 0.02710086
9 -0.009389125 0.03060530
10 -0.377361453 -0.08580198
18 -0.020083220 -0.04031167
25 0.236752837 -0.12199089
27 -0.370532471 0.08710922
39 0.014124262 -0.10817729
49 0.403944819 0.12045772
50 -0.156948207 0.19927226
$call
outlier.default(veg = nveg, thresh = 0.2, y = 0.5)
attr(,"class")
[1] "outlier"
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