927 lines
42 KiB
Plaintext
927 lines
42 KiB
Plaintext
|
|
||
|
|
R version 4.2.0 Patched (2022-05-13 r82353) -- "Vigorous Calisthenics"
|
||
|
|
Copyright (C) 2022 The R Foundation for Statistical Computing
|
||
|
|
Platform: x86_64-pc-linux-gnu (64-bit)
|
||
|
|
|
||
|
|
R is free software and comes with ABSOLUTELY NO WARRANTY.
|
||
|
|
You are welcome to redistribute it under certain conditions.
|
||
|
|
Type 'license()' or 'licence()' for distribution details.
|
||
|
|
|
||
|
|
R is a collaborative project with many contributors.
|
||
|
|
Type 'contributors()' for more information and
|
||
|
|
'citation()' on how to cite R or R packages in publications.
|
||
|
|
|
||
|
|
Type 'demo()' for some demos, 'help()' for on-line help, or
|
||
|
|
'help.start()' for an HTML browser interface to help.
|
||
|
|
Type 'q()' to quit R.
|
||
|
|
|
||
|
|
> ## For different cluster versions
|
||
|
|
>
|
||
|
|
> require(cluster)
|
||
|
|
Loading required package: cluster
|
||
|
|
>
|
||
|
|
> if(interactive()) print(packageDescription("cluster"))
|
||
|
|
>
|
||
|
|
> ## trivial cases should 'work':
|
||
|
|
> daisy(cbind(1))
|
||
|
|
Dissimilarities :
|
||
|
|
dissimilarity(0)
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 1
|
||
|
|
> (d10 <- daisy(matrix(0., 1,0))); str(d10)
|
||
|
|
Dissimilarities :
|
||
|
|
dissimilarity(0)
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 1
|
||
|
|
'dissimilarity' num(0)
|
||
|
|
- attr(*, "Size")= int 1
|
||
|
|
- attr(*, "Metric")= chr "euclidean"
|
||
|
|
> d01 <- daisy(matrix(0., 0,1))
|
||
|
|
> if(paste(R.version$major, R.version$minor, sep=".") >= "2.1.0")
|
||
|
|
+ print(d01)
|
||
|
|
Dissimilarities :
|
||
|
|
dissimilarity(0)
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 0
|
||
|
|
> str(d01)
|
||
|
|
'dissimilarity' num(0)
|
||
|
|
- attr(*, "Size")= int 0
|
||
|
|
- attr(*, "Metric")= chr "euclidean"
|
||
|
|
> d32 <- data.frame(eins=c("A"=1,"B"=1,"C"=1), zwei=c(2,2,2))
|
||
|
|
> daisy(d32)
|
||
|
|
Dissimilarities :
|
||
|
|
A B
|
||
|
|
B 0
|
||
|
|
C 0 0
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 3
|
||
|
|
> daisy(d32, stand = TRUE)
|
||
|
|
Dissimilarities :
|
||
|
|
A B
|
||
|
|
B 0
|
||
|
|
C 0 0
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 3
|
||
|
|
Warning message:
|
||
|
|
In daisy(d32, stand = TRUE) :
|
||
|
|
'x' has constant columns 1, 2; these are standardized to 0
|
||
|
|
> daisy(d32, type = list(ordratio="zwei"))
|
||
|
|
Dissimilarities :
|
||
|
|
A B
|
||
|
|
B 0
|
||
|
|
C 0 0
|
||
|
|
|
||
|
|
Metric : mixed ; Types = I, T
|
||
|
|
Number of objects : 3
|
||
|
|
>
|
||
|
|
>
|
||
|
|
> str(d5 <- data.frame(a= c(0, 0, 0,1,0,0, 0,0,1, 0,NA),
|
||
|
|
+ b= c(NA,0, 1,1,0,1, 0,1,0, 1,0),
|
||
|
|
+ c= c(0, 1, 1,0,1,NA,1,0,1, 0,NA),
|
||
|
|
+ d= c(1, 1, 0,1,0,0, 0,0,0, 1,0),
|
||
|
|
+ e= c(1, NA,0,1,0,0, 0,0,NA,1,1)))
|
||
|
|
'data.frame': 11 obs. of 5 variables:
|
||
|
|
$ a: num 0 0 0 1 0 0 0 0 1 0 ...
|
||
|
|
$ b: num NA 0 1 1 0 1 0 1 0 1 ...
|
||
|
|
$ c: num 0 1 1 0 1 NA 1 0 1 0 ...
|
||
|
|
$ d: num 1 1 0 1 0 0 0 0 0 1 ...
|
||
|
|
$ e: num 1 NA 0 1 0 0 0 0 NA 1 ...
|
||
|
|
> (d0 <- daisy(d5))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7 8
|
||
|
|
2 1.290994
|
||
|
|
3 1.936492 1.581139
|
||
|
|
4 1.118034 1.936492 2.000000
|
||
|
|
5 1.936492 1.118034 1.000000 2.236068
|
||
|
|
6 1.825742 1.825742 0.000000 1.936492 1.118034
|
||
|
|
7 1.936492 1.118034 1.000000 2.236068 0.000000 1.118034
|
||
|
|
8 1.581139 1.936492 1.000000 1.732051 1.414214 0.000000 1.414214
|
||
|
|
9 2.236068 1.581139 1.581139 1.936492 1.118034 1.825742 1.118034 1.936492
|
||
|
|
10 0.000000 1.581139 1.732051 1.000000 2.000000 1.581139 2.000000 1.414214
|
||
|
|
11 1.581139 1.581139 1.825742 1.825742 1.290994 1.825742 1.290994 1.825742
|
||
|
|
9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10 2.236068
|
||
|
|
11 0.000000 1.825742
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5) : binary variable(s) 1, 2, 3, 4, 5 treated as interval scaled
|
||
|
|
> (d1 <- daisy(d5, type = list(asymm = 1:5)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.5000000
|
||
|
|
3 1.0000000 0.6666667
|
||
|
|
4 0.3333333 0.7500000 0.8000000
|
||
|
|
5 1.0000000 0.5000000 0.5000000 1.0000000
|
||
|
|
6 1.0000000 1.0000000 0.0000000 0.7500000 1.0000000
|
||
|
|
7 1.0000000 0.5000000 0.5000000 1.0000000 0.0000000 1.0000000
|
||
|
|
8 1.0000000 1.0000000 0.5000000 0.7500000 1.0000000 0.0000000 1.0000000
|
||
|
|
9 1.0000000 0.6666667 0.6666667 0.7500000 0.5000000 1.0000000 0.5000000
|
||
|
|
10 0.0000000 0.6666667 0.7500000 0.2500000 1.0000000 0.6666667 1.0000000
|
||
|
|
11 0.5000000 1.0000000 1.0000000 0.6666667 1.0000000 1.0000000 1.0000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.6666667 1.0000000
|
||
|
|
11 1.0000000 NA 0.6666667
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, A, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
> (d2 <- daisy(d5, type = list(symm = 1:2, asymm= 3:5)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.3333333
|
||
|
|
3 0.7500000 0.5000000
|
||
|
|
4 0.3333333 0.7500000 0.8000000
|
||
|
|
5 0.7500000 0.2500000 0.3333333 1.0000000
|
||
|
|
6 0.6666667 0.6666667 0.0000000 0.7500000 0.5000000
|
||
|
|
7 0.7500000 0.2500000 0.3333333 1.0000000 0.0000000 0.5000000
|
||
|
|
8 0.6666667 0.7500000 0.3333333 0.7500000 0.6666667 0.0000000 0.6666667
|
||
|
|
9 1.0000000 0.5000000 0.6666667 0.7500000 0.3333333 1.0000000 0.3333333
|
||
|
|
10 0.0000000 0.5000000 0.6000000 0.2500000 0.8000000 0.5000000 0.8000000
|
||
|
|
11 0.5000000 0.5000000 1.0000000 0.6666667 0.5000000 1.0000000 0.5000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.5000000 1.0000000
|
||
|
|
11 1.0000000 0.0000000 0.6666667
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, S, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
> (d2.<- daisy(d5, type = list( asymm= 3:5)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.3333333
|
||
|
|
3 0.7500000 0.5000000
|
||
|
|
4 0.3333333 0.7500000 0.8000000
|
||
|
|
5 0.7500000 0.2500000 0.3333333 1.0000000
|
||
|
|
6 0.6666667 0.6666667 0.0000000 0.7500000 0.5000000
|
||
|
|
7 0.7500000 0.2500000 0.3333333 1.0000000 0.0000000 0.5000000
|
||
|
|
8 0.6666667 0.7500000 0.3333333 0.7500000 0.6666667 0.0000000 0.6666667
|
||
|
|
9 1.0000000 0.5000000 0.6666667 0.7500000 0.3333333 1.0000000 0.3333333
|
||
|
|
10 0.0000000 0.5000000 0.6000000 0.2500000 0.8000000 0.5000000 0.8000000
|
||
|
|
11 0.5000000 0.5000000 1.0000000 0.6666667 0.5000000 1.0000000 0.5000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.5000000 1.0000000
|
||
|
|
11 1.0000000 0.0000000 0.6666667
|
||
|
|
|
||
|
|
Metric : mixed ; Types = I, I, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5, type = list(asymm = 3:5)) :
|
||
|
|
binary variable(s) 1, 2 treated as interval scaled
|
||
|
|
> stopifnot(identical(c(d2), c(d2.)))
|
||
|
|
> (dS <- daisy(d5, stand = TRUE))# gave error in some versions
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7 8
|
||
|
|
2 2.614264
|
||
|
|
3 4.010913 3.291786
|
||
|
|
4 3.493856 4.725761 4.757684
|
||
|
|
5 4.010913 2.415752 2.000000 5.160965
|
||
|
|
6 3.823025 3.801028 0.000000 4.813384 2.236068
|
||
|
|
7 4.010913 2.415752 2.000000 5.160965 0.000000 2.236068
|
||
|
|
8 3.310837 3.995202 2.025000 4.305222 2.846160 0.000000 2.846160
|
||
|
|
9 5.558018 4.247692 4.148136 3.995202 3.493856 4.789855 3.493856 4.725761
|
||
|
|
10 0.000000 3.182103 3.587469 3.125000 4.107303 3.310837 4.107303 2.961302
|
||
|
|
11 3.416389 3.416389 3.674376 3.801028 2.614264 3.674376 2.614264 3.674376
|
||
|
|
9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10 5.307417
|
||
|
|
11 0.000000 3.801028
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5, stand = TRUE) :
|
||
|
|
binary variable(s) 1, 2, 3, 4, 5 treated as interval scaled
|
||
|
|
> stopifnot(all.equal(as.vector(summary(c(dS), digits=9)),
|
||
|
|
+ c(0, 2.6142638, 3.4938562, 3.2933687, 4.0591077, 5.5580177),
|
||
|
|
+ tol = 1e-7))# 7.88e-9
|
||
|
|
>
|
||
|
|
> d5[,4] <- 1 # binary with only one instead of two values
|
||
|
|
> (d0 <- daisy(d5))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7 8
|
||
|
|
2 1.290994
|
||
|
|
3 1.581139 1.118034
|
||
|
|
4 1.118034 1.936492 1.732051
|
||
|
|
5 1.581139 0.000000 1.000000 2.000000
|
||
|
|
6 1.290994 1.290994 0.000000 1.581139 1.118034
|
||
|
|
7 1.581139 0.000000 1.000000 2.000000 0.000000 1.118034
|
||
|
|
8 1.118034 1.581139 1.000000 1.414214 1.414214 0.000000 1.414214
|
||
|
|
9 1.825742 1.118034 1.581139 1.581139 1.118034 1.825742 1.118034 1.936492
|
||
|
|
10 0.000000 1.581139 1.414214 1.000000 1.732051 1.118034 1.732051 1.000000
|
||
|
|
11 0.000000 0.000000 1.825742 1.290994 1.290994 1.825742 1.290994 1.825742
|
||
|
|
9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10 1.936492
|
||
|
|
11 0.000000 1.290994
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5) : binary variable(s) 1, 2, 3, 5 treated as interval scaled
|
||
|
|
> (d1 <- daisy(d5, type = list(asymm = 1:5)))# 2 NAs
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 1.0000000
|
||
|
|
3 1.0000000 0.5000000
|
||
|
|
4 0.5000000 1.0000000 0.7500000
|
||
|
|
5 1.0000000 0.0000000 0.5000000 1.0000000
|
||
|
|
6 1.0000000 1.0000000 0.0000000 0.6666667 1.0000000
|
||
|
|
7 1.0000000 0.0000000 0.5000000 1.0000000 0.0000000 1.0000000
|
||
|
|
8 1.0000000 1.0000000 0.5000000 0.6666667 1.0000000 0.0000000 1.0000000
|
||
|
|
9 1.0000000 0.5000000 0.6666667 0.6666667 0.5000000 1.0000000 0.5000000
|
||
|
|
10 0.0000000 1.0000000 0.6666667 0.3333333 1.0000000 0.5000000 1.0000000
|
||
|
|
11 0.0000000 NA 1.0000000 0.5000000 1.0000000 1.0000000 1.0000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.5000000 1.0000000
|
||
|
|
11 1.0000000 NA 0.5000000
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, A, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5, type = list(asymm = 1:5)) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
> (d2 <- daisy(d5, type = list(symm = 1:2, asymm= 3:5)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.5000000
|
||
|
|
3 0.6666667 0.3333333
|
||
|
|
4 0.5000000 1.0000000 0.7500000
|
||
|
|
5 0.6666667 0.0000000 0.3333333 1.0000000
|
||
|
|
6 0.5000000 0.5000000 0.0000000 0.6666667 0.5000000
|
||
|
|
7 0.6666667 0.0000000 0.3333333 1.0000000 0.0000000 0.5000000
|
||
|
|
8 0.5000000 0.6666667 0.3333333 0.6666667 0.6666667 0.0000000 0.6666667
|
||
|
|
9 1.0000000 0.3333333 0.6666667 0.6666667 0.3333333 1.0000000 0.3333333
|
||
|
|
10 0.0000000 0.6666667 0.5000000 0.3333333 0.7500000 0.3333333 0.7500000
|
||
|
|
11 0.0000000 0.0000000 1.0000000 0.5000000 0.5000000 1.0000000 0.5000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.3333333 1.0000000
|
||
|
|
11 1.0000000 0.0000000 0.5000000
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, S, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
Warning message:
|
||
|
|
In daisy(d5, type = list(symm = 1:2, asymm = 3:5)) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
> (d2.<- daisy(d5, type = list( asymm= 3:5)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.5000000
|
||
|
|
3 0.6666667 0.3333333
|
||
|
|
4 0.5000000 1.0000000 0.7500000
|
||
|
|
5 0.6666667 0.0000000 0.3333333 1.0000000
|
||
|
|
6 0.5000000 0.5000000 0.0000000 0.6666667 0.5000000
|
||
|
|
7 0.6666667 0.0000000 0.3333333 1.0000000 0.0000000 0.5000000
|
||
|
|
8 0.5000000 0.6666667 0.3333333 0.6666667 0.6666667 0.0000000 0.6666667
|
||
|
|
9 1.0000000 0.3333333 0.6666667 0.6666667 0.3333333 1.0000000 0.3333333
|
||
|
|
10 0.0000000 0.6666667 0.5000000 0.3333333 0.7500000 0.3333333 0.7500000
|
||
|
|
11 0.0000000 0.0000000 1.0000000 0.5000000 0.5000000 1.0000000 0.5000000
|
||
|
|
8 9 10
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 1.0000000
|
||
|
|
10 0.3333333 1.0000000
|
||
|
|
11 1.0000000 0.0000000 0.5000000
|
||
|
|
|
||
|
|
Metric : mixed ; Types = I, I, A, A, A
|
||
|
|
Number of objects : 11
|
||
|
|
Warning messages:
|
||
|
|
1: In daisy(d5, type = list(asymm = 3:5)) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
2: In daisy(d5, type = list(asymm = 3:5)) :
|
||
|
|
binary variable(s) 1, 2 treated as interval scaled
|
||
|
|
> ## better leave away the constant variable: it has no effect:
|
||
|
|
> stopifnot(identical(c(d1), c(daisy(d5[,-4], type = list(asymm = 1:4)))))
|
||
|
|
>
|
||
|
|
> ###---- Trivial "binary only" matrices (not data frames) did fail:
|
||
|
|
>
|
||
|
|
> x <- matrix(0, 2, 2)
|
||
|
|
> dimnames(x)[[2]] <- c("A", "B")## colnames<- is missing in S+
|
||
|
|
> daisy(x, type = list(symm= "B", asymm="A"))
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 0
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, S
|
||
|
|
Number of objects : 2
|
||
|
|
Warning message:
|
||
|
|
In daisy(x, type = list(symm = "B", asymm = "A")) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
> daisy(x, type = list(symm= "B"))# 0 too
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 0
|
||
|
|
|
||
|
|
Metric : mixed ; Types = I, S
|
||
|
|
Number of objects : 2
|
||
|
|
Warning message:
|
||
|
|
In daisy(x, type = list(symm = "B")) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
>
|
||
|
|
> x2 <- x; x2[2,2] <- 1
|
||
|
|
> daisy(x2, type= list(symm = "B"))# |-> 0.5 (gives 1 in S+)
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 0.5
|
||
|
|
|
||
|
|
Metric : mixed ; Types = I, S
|
||
|
|
Number of objects : 2
|
||
|
|
> daisy(x2, type= list(symm = "B", asymm="A"))# 1
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 1
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, S
|
||
|
|
Number of objects : 2
|
||
|
|
Warning message:
|
||
|
|
In daisy(x2, type = list(symm = "B", asymm = "A")) :
|
||
|
|
at least one binary variable has not 2 different levels.
|
||
|
|
>
|
||
|
|
> x3 <- x; x3[] <- diag(2)
|
||
|
|
> daisy(x3) # warning: both as interval scaled -> sqrt(2)
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 1.414214
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 2
|
||
|
|
> daisy(x3, type= list(symm="B", asymm="A"))# 1
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 1
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, S
|
||
|
|
Number of objects : 2
|
||
|
|
> daisy(x3, type= list(symm =c("B","A"))) # 1, S+: sqrt(2)
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 1
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, S
|
||
|
|
Number of objects : 2
|
||
|
|
> daisy(x3, type= list(asymm=c("B","A"))) # 1, S+ : sqrt(2)
|
||
|
|
Dissimilarities :
|
||
|
|
1
|
||
|
|
2 1
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, A
|
||
|
|
Number of objects : 2
|
||
|
|
>
|
||
|
|
> x4 <- rbind(x3, 1)
|
||
|
|
> daisy(x4, type= list(symm="B", asymm="A"))# 1 0.5 0.5
|
||
|
|
Dissimilarities :
|
||
|
|
1 2
|
||
|
|
2 1.0
|
||
|
|
3 0.5 0.5
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, S
|
||
|
|
Number of objects : 3
|
||
|
|
> daisy(x4, type= list(symm=c("B","A"))) # dito; S+ : 1.41 1 1
|
||
|
|
Dissimilarities :
|
||
|
|
1 2
|
||
|
|
2 1.0
|
||
|
|
3 0.5 0.5
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, S
|
||
|
|
Number of objects : 3
|
||
|
|
> daisy(x4, type= list(asymm=c("A","B"))) # dito, dito
|
||
|
|
Dissimilarities :
|
||
|
|
1 2
|
||
|
|
2 1.0
|
||
|
|
3 0.5 0.5
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, A
|
||
|
|
Number of objects : 3
|
||
|
|
>
|
||
|
|
>
|
||
|
|
>
|
||
|
|
> ## ----------- example(daisy) -----------------------
|
||
|
|
>
|
||
|
|
> data(flower)
|
||
|
|
> data(agriculture)
|
||
|
|
>
|
||
|
|
> ## Example 1 in ref:
|
||
|
|
> ## Dissimilarities using Euclidean metric and without standardization
|
||
|
|
> (d.agr <- daisy(agriculture, metric = "euclidean", stand = FALSE))
|
||
|
|
Dissimilarities :
|
||
|
|
B DK D GR E F IRL
|
||
|
|
DK 5.408327
|
||
|
|
D 2.061553 3.405877
|
||
|
|
GR 22.339651 22.570113 22.661200
|
||
|
|
E 9.818350 11.182576 10.394710 12.567418
|
||
|
|
F 3.448188 3.512834 2.657066 20.100995 8.060397
|
||
|
|
IRL 12.747549 13.306014 13.080138 9.604166 3.140064 10.564563
|
||
|
|
I 5.803447 5.470832 5.423099 17.383325 5.727128 2.773085 7.920859
|
||
|
|
L 4.275512 2.220360 2.300000 24.035391 12.121056 4.060788 14.569145
|
||
|
|
NL 1.649242 5.096077 2.435159 20.752349 8.280097 2.202272 11.150785
|
||
|
|
P 17.236299 17.864490 17.664088 5.162364 7.430343 15.164432 4.601087
|
||
|
|
UK 2.828427 8.052950 4.850773 21.485344 8.984431 5.303772 12.103718
|
||
|
|
I L NL P
|
||
|
|
DK
|
||
|
|
D
|
||
|
|
GR
|
||
|
|
E
|
||
|
|
F
|
||
|
|
IRL
|
||
|
|
I
|
||
|
|
L 6.660330
|
||
|
|
NL 4.204759 4.669047
|
||
|
|
P 12.515990 19.168985 15.670673
|
||
|
|
UK 6.723095 7.102112 3.124100 16.323296
|
||
|
|
|
||
|
|
Metric : euclidean
|
||
|
|
Number of objects : 12
|
||
|
|
> (d.agr2 <- daisy(agriculture, metric = "manhattan"))
|
||
|
|
Dissimilarities :
|
||
|
|
B DK D GR E F IRL I L NL P
|
||
|
|
DK 7.5
|
||
|
|
D 2.7 4.8
|
||
|
|
GR 30.4 31.9 31.5
|
||
|
|
E 13.6 15.1 14.7 16.8
|
||
|
|
F 4.3 3.8 3.4 28.1 11.3
|
||
|
|
IRL 17.2 18.7 18.3 13.2 3.6 14.9
|
||
|
|
I 6.0 7.5 7.1 24.4 7.6 3.7 11.2
|
||
|
|
L 5.0 2.5 2.3 33.8 17.0 5.7 20.6 9.4
|
||
|
|
NL 2.0 6.3 3.1 28.4 11.6 3.1 15.2 4.4 5.4
|
||
|
|
P 23.7 25.2 24.8 6.7 10.1 21.4 6.5 17.7 27.1 21.7
|
||
|
|
UK 3.2 10.7 5.9 28.0 11.2 7.5 14.8 8.8 8.2 4.4 21.3
|
||
|
|
|
||
|
|
Metric : manhattan
|
||
|
|
Number of objects : 12
|
||
|
|
>
|
||
|
|
>
|
||
|
|
> ## Example 2 in ref
|
||
|
|
> (dfl0 <- daisy(flower))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.8875408
|
||
|
|
3 0.5272467 0.5147059
|
||
|
|
4 0.3517974 0.5504493 0.5651552
|
||
|
|
5 0.4115605 0.6226307 0.3726307 0.6383578
|
||
|
|
6 0.2269199 0.6606209 0.3003268 0.4189951 0.3443627
|
||
|
|
7 0.2876225 0.5999183 0.4896242 0.3435866 0.4197712 0.1892974
|
||
|
|
8 0.4234069 0.4641340 0.6038399 0.2960376 0.4673203 0.5714869 0.4107843
|
||
|
|
9 0.5808824 0.4316585 0.4463644 0.8076797 0.3306781 0.5136846 0.5890931
|
||
|
|
10 0.6094363 0.4531046 0.4678105 0.5570670 0.3812908 0.4119281 0.5865196
|
||
|
|
11 0.3278595 0.7096814 0.5993873 0.6518791 0.3864788 0.4828840 0.5652369
|
||
|
|
12 0.4267565 0.5857843 0.6004902 0.5132761 0.5000817 0.5248366 0.6391340
|
||
|
|
13 0.5196487 0.5248366 0.5395425 0.7464461 0.2919118 0.4524510 0.5278595
|
||
|
|
14 0.2926062 0.5949346 0.6096405 0.3680147 0.5203431 0.3656863 0.5049837
|
||
|
|
15 0.6221814 0.3903595 0.5300654 0.5531454 0.4602124 0.5091503 0.3345588
|
||
|
|
16 0.6935866 0.3575163 0.6222222 0.3417892 0.7301471 0.5107843 0.4353758
|
||
|
|
17 0.7765114 0.1904412 0.5801471 0.4247141 0.6880719 0.5937092 0.5183007
|
||
|
|
18 0.4610294 0.4515114 0.7162173 0.4378268 0.4755310 0.6438317 0.4692402
|
||
|
|
8 9 10 11 12 13 14
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 0.6366422
|
||
|
|
10 0.6639706 0.4256127
|
||
|
|
11 0.4955474 0.4308007 0.3948121
|
||
|
|
12 0.4216503 0.4194036 0.3812092 0.2636029
|
||
|
|
13 0.5754085 0.2181781 0.3643791 0.3445670 0.2331699
|
||
|
|
14 0.4558007 0.4396650 0.3609477 0.2838644 0.1591503 0.3784314
|
||
|
|
15 0.4512255 0.2545343 0.4210784 0.4806781 0.4295752 0.3183007 0.4351307
|
||
|
|
16 0.6378268 0.6494690 0.3488562 0.7436683 0.6050654 0.5882353 0.4598039
|
||
|
|
17 0.4707516 0.6073938 0.3067810 0.7015931 0.5629902 0.5461601 0.5427288
|
||
|
|
18 0.1417892 0.5198529 0.8057598 0.5359477 0.5495507 0.5733252 0.5698121
|
||
|
|
15 16 17
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10
|
||
|
|
11
|
||
|
|
12
|
||
|
|
13
|
||
|
|
14
|
||
|
|
15
|
||
|
|
16 0.3949346
|
||
|
|
17 0.3528595 0.1670752
|
||
|
|
18 0.5096814 0.7796160 0.6125408
|
||
|
|
|
||
|
|
Metric : mixed ; Types = N, N, N, N, O, O, I, I
|
||
|
|
Number of objects : 18
|
||
|
|
> stopifnot(identical(c(dfl0),
|
||
|
|
+ c(daisy(flower, type = list(symm = 1)))) &&
|
||
|
|
+ identical(c(dfl0),
|
||
|
|
+ c(daisy(flower, type = list(symm = 2)))) &&
|
||
|
|
+ identical(c(dfl0),
|
||
|
|
+ c(daisy(flower, type = list(symm = 3)))) &&
|
||
|
|
+ identical(c(dfl0),
|
||
|
|
+ c(daisy(flower, type = list(symm = c(1,3)))))
|
||
|
|
+ )
|
||
|
|
>
|
||
|
|
> (dfl1 <- daisy(flower, type = list(asymm = 3)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.8875408
|
||
|
|
3 0.5272467 0.5882353
|
||
|
|
4 0.3517974 0.5504493 0.5651552
|
||
|
|
5 0.4115605 0.7115780 0.4258637 0.6383578
|
||
|
|
6 0.2269199 0.7549953 0.3432306 0.4189951 0.3935574
|
||
|
|
7 0.2876225 0.6856209 0.5595705 0.3435866 0.4797386 0.2163399
|
||
|
|
8 0.4234069 0.4641340 0.6038399 0.2960376 0.4673203 0.5714869 0.4107843
|
||
|
|
9 0.5808824 0.4933240 0.5101307 0.8076797 0.3779178 0.5870682 0.6732493
|
||
|
|
10 0.6094363 0.5178338 0.5346405 0.5570670 0.4357610 0.4707750 0.6703081
|
||
|
|
11 0.3278595 0.7096814 0.5993873 0.6518791 0.3864788 0.4828840 0.5652369
|
||
|
|
12 0.4267565 0.5857843 0.6004902 0.5132761 0.5000817 0.5248366 0.6391340
|
||
|
|
13 0.5196487 0.5998133 0.6166200 0.7464461 0.3336134 0.5170868 0.6032680
|
||
|
|
14 0.2926062 0.5949346 0.6096405 0.3680147 0.5203431 0.3656863 0.5049837
|
||
|
|
15 0.6221814 0.4461251 0.6057890 0.5531454 0.5259570 0.5818861 0.3823529
|
||
|
|
16 0.6935866 0.4085901 0.7111111 0.3417892 0.8344538 0.5837535 0.4975724
|
||
|
|
17 0.7765114 0.2176471 0.6630252 0.4247141 0.7863679 0.6785247 0.5923436
|
||
|
|
18 0.4610294 0.4515114 0.7162173 0.4378268 0.4755310 0.6438317 0.4692402
|
||
|
|
8 9 10 11 12 13 14
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 0.6366422
|
||
|
|
10 0.6639706 0.4864146
|
||
|
|
11 0.4955474 0.4308007 0.3948121
|
||
|
|
12 0.4216503 0.4194036 0.3812092 0.2636029
|
||
|
|
13 0.5754085 0.2493464 0.4164332 0.3445670 0.2331699
|
||
|
|
14 0.4558007 0.4396650 0.3609477 0.2838644 0.1591503 0.3784314
|
||
|
|
15 0.4512255 0.2908964 0.4812325 0.4806781 0.4295752 0.3637722 0.4351307
|
||
|
|
16 0.6378268 0.7422502 0.3986928 0.7436683 0.6050654 0.6722689 0.4598039
|
||
|
|
17 0.4707516 0.6941643 0.3506069 0.7015931 0.5629902 0.6241830 0.5427288
|
||
|
|
18 0.1417892 0.5198529 0.8057598 0.5359477 0.5495507 0.5733252 0.5698121
|
||
|
|
15 16 17
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10
|
||
|
|
11
|
||
|
|
12
|
||
|
|
13
|
||
|
|
14
|
||
|
|
15
|
||
|
|
16 0.4513539
|
||
|
|
17 0.4032680 0.1909430
|
||
|
|
18 0.5096814 0.7796160 0.6125408
|
||
|
|
|
||
|
|
Metric : mixed ; Types = N, N, A, N, O, O, I, I
|
||
|
|
Number of objects : 18
|
||
|
|
> (dfl2 <- daisy(flower, type = list(asymm = c(1, 3), ordratio = 7)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.9007353
|
||
|
|
3 0.6176471 0.5882353
|
||
|
|
4 0.4226891 0.5455882 0.6403361
|
||
|
|
5 0.4806723 0.7369748 0.5264706 0.7605042
|
||
|
|
6 0.2823529 0.7470588 0.3911765 0.4764706 0.4980392
|
||
|
|
7 0.3310924 0.6983193 0.6676471 0.4109244 0.5745098 0.2764706
|
||
|
|
8 0.5100840 0.4544118 0.6789916 0.3327731 0.5705882 0.6563025 0.4932773
|
||
|
|
9 0.5808824 0.5084034 0.5252101 0.8257353 0.3882353 0.6100840 0.6756303
|
||
|
|
10 0.6323529 0.5067227 0.5235294 0.5522059 0.4722689 0.4739496 0.6941176
|
||
|
|
11 0.3389706 0.7117647 0.6014706 0.6588235 0.4066176 0.4919118 0.5742647
|
||
|
|
12 0.4441176 0.5816176 0.5963235 0.5139706 0.5264706 0.5220588 0.6544118
|
||
|
|
13 0.5286765 0.6252101 0.6420168 0.7735294 0.3336134 0.5504202 0.6159664
|
||
|
|
14 0.3044118 0.5963235 0.6110294 0.3742647 0.5411765 0.3573529 0.5147059
|
||
|
|
15 0.6242647 0.4588235 0.6184874 0.5691176 0.5386555 0.6025210 0.3823529
|
||
|
|
16 0.6845588 0.3831933 0.6857143 0.3147059 0.8344538 0.5504202 0.4848739
|
||
|
|
17 0.7897059 0.2176471 0.6630252 0.4198529 0.8117647 0.6705882 0.6050420
|
||
|
|
18 0.5268908 0.4647059 0.8336134 0.5210084 0.5537815 0.7588235 0.5386555
|
||
|
|
8 9 10 11 12 13 14
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 0.6595588
|
||
|
|
10 0.6639706 0.5126050
|
||
|
|
11 0.5073529 0.4419118 0.4066176
|
||
|
|
12 0.4272059 0.4367647 0.3867647 0.2698529
|
||
|
|
13 0.6073529 0.2596639 0.4529412 0.3647059 0.2595588
|
||
|
|
14 0.4669118 0.4514706 0.3720588 0.2845588 0.1647059 0.3992647
|
||
|
|
15 0.4720588 0.2932773 0.5050420 0.4897059 0.4448529 0.3764706 0.4448529
|
||
|
|
16 0.6058824 0.7319328 0.3621849 0.7235294 0.5786765 0.6722689 0.4389706
|
||
|
|
17 0.4610294 0.7092437 0.3394958 0.7036765 0.5588235 0.6495798 0.5441176
|
||
|
|
18 0.1882353 0.5198529 0.8286765 0.5470588 0.5669118 0.5823529 0.5816176
|
||
|
|
15 16 17
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10
|
||
|
|
11
|
||
|
|
12
|
||
|
|
13
|
||
|
|
14
|
||
|
|
15
|
||
|
|
16 0.4386555
|
||
|
|
17 0.4159664 0.1655462
|
||
|
|
18 0.5117647 0.7705882 0.6257353
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, N, A, N, O, O, T, I
|
||
|
|
Number of objects : 18
|
||
|
|
> (dfl3 <- daisy(flower, type = list(asymm = 1:3)))
|
||
|
|
Dissimilarities :
|
||
|
|
1 2 3 4 5 6 7
|
||
|
|
2 0.8875408
|
||
|
|
3 0.6025677 0.5882353
|
||
|
|
4 0.4020542 0.6290850 0.6458917
|
||
|
|
5 0.4703548 0.7115780 0.4968410 0.7295518
|
||
|
|
6 0.2593371 0.7549953 0.4004357 0.4788515 0.4591503
|
||
|
|
7 0.3287115 0.7998911 0.6528322 0.4581155 0.5596950 0.2523965
|
||
|
|
8 0.4838936 0.5304388 0.6901027 0.3947168 0.5340803 0.6531279 0.5477124
|
||
|
|
9 0.5808824 0.4933240 0.5101307 0.8076797 0.3779178 0.5870682 0.6732493
|
||
|
|
10 0.6094363 0.5178338 0.5346405 0.5570670 0.4357610 0.4707750 0.6703081
|
||
|
|
11 0.3278595 0.7096814 0.5993873 0.6518791 0.3864788 0.4828840 0.5652369
|
||
|
|
12 0.4267565 0.5857843 0.6004902 0.5132761 0.5000817 0.5248366 0.6391340
|
||
|
|
13 0.5196487 0.5998133 0.6166200 0.7464461 0.3336134 0.5170868 0.6032680
|
||
|
|
14 0.2926062 0.5949346 0.6096405 0.3680147 0.5203431 0.3656863 0.5049837
|
||
|
|
15 0.6221814 0.5204793 0.6057890 0.6321662 0.5259570 0.5818861 0.4460784
|
||
|
|
16 0.6935866 0.4766885 0.7111111 0.3906162 0.8344538 0.5837535 0.5805011
|
||
|
|
17 0.7765114 0.2539216 0.6630252 0.4853875 0.7863679 0.6785247 0.6910675
|
||
|
|
18 0.5268908 0.5160131 0.8185341 0.5837691 0.5434641 0.7358077 0.6256536
|
||
|
|
8 9 10 11 12 13 14
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9 0.6366422
|
||
|
|
10 0.6639706 0.4864146
|
||
|
|
11 0.4955474 0.4308007 0.3948121
|
||
|
|
12 0.4216503 0.4194036 0.3812092 0.2636029
|
||
|
|
13 0.5754085 0.2493464 0.4164332 0.3445670 0.2331699
|
||
|
|
14 0.4558007 0.4396650 0.3609477 0.2838644 0.1591503 0.3784314
|
||
|
|
15 0.5156863 0.2908964 0.4812325 0.4806781 0.4295752 0.3637722 0.4351307
|
||
|
|
16 0.7289449 0.7422502 0.3986928 0.7436683 0.6050654 0.6722689 0.4598039
|
||
|
|
17 0.5380019 0.6941643 0.3506069 0.7015931 0.5629902 0.6241830 0.5427288
|
||
|
|
18 0.1890523 0.5198529 0.8057598 0.5359477 0.5495507 0.5733252 0.5698121
|
||
|
|
15 16 17
|
||
|
|
2
|
||
|
|
3
|
||
|
|
4
|
||
|
|
5
|
||
|
|
6
|
||
|
|
7
|
||
|
|
8
|
||
|
|
9
|
||
|
|
10
|
||
|
|
11
|
||
|
|
12
|
||
|
|
13
|
||
|
|
14
|
||
|
|
15
|
||
|
|
16 0.5265795
|
||
|
|
17 0.4704793 0.2227669
|
||
|
|
18 0.5824930 0.8909897 0.7000467
|
||
|
|
|
||
|
|
Metric : mixed ; Types = A, A, A, N, O, O, I, I
|
||
|
|
Number of objects : 18
|
||
|
|
>
|
||
|
|
> ## --- animals
|
||
|
|
> data(animals)
|
||
|
|
> d0 <- daisy(animals)
|
||
|
|
Warning message:
|
||
|
|
In daisy(animals) :
|
||
|
|
binary variable(s) 1, 2, 3, 4, 5, 6 treated as interval scaled
|
||
|
|
>
|
||
|
|
> d1 <- daisy(animals - 1, type=list(asymm=c(2,4)))
|
||
|
|
Warning message:
|
||
|
|
In daisy(animals - 1, type = list(asymm = c(2, 4))) :
|
||
|
|
binary variable(s) 1, 3, 5, 6 treated as interval scaled
|
||
|
|
> (d2 <- daisy(animals - 1, type=list(symm = c(1,3,5,6), asymm=c(2,4))))
|
||
|
|
Dissimilarities :
|
||
|
|
ant bee cat cpl chi cow duc
|
||
|
|
bee 0.4000000
|
||
|
|
cat 1.0000000 0.8000000
|
||
|
|
cpl 0.5000000 0.4000000 0.5000000
|
||
|
|
chi 0.8000000 0.6666667 0.4000000 0.8000000
|
||
|
|
cow 0.7500000 0.6000000 0.2500000 0.7500000 0.2000000
|
||
|
|
duc 0.6000000 0.6000000 0.6000000 1.0000000 0.5000000 0.4000000
|
||
|
|
eag 0.8333333 0.8333333 0.5000000 0.8333333 0.5000000 0.6666667 0.3333333
|
||
|
|
ele 0.6000000 0.8333333 0.6000000 1.0000000 0.2000000 0.4000000 0.3333333
|
||
|
|
fly 0.4000000 0.4000000 0.8000000 0.4000000 1.0000000 1.0000000 0.6000000
|
||
|
|
fro 0.5000000 0.8000000 0.7500000 0.7500000 0.5000000 0.7500000 0.6000000
|
||
|
|
her 0.2500000 0.6000000 0.7500000 0.7500000 0.6000000 0.5000000 0.4000000
|
||
|
|
lio 0.7500000 0.6000000 0.2500000 0.7500000 0.0000000 0.0000000 0.4000000
|
||
|
|
liz 0.5000000 0.8000000 0.5000000 0.5000000 0.8000000 0.7500000 0.6000000
|
||
|
|
lob 0.0000000 0.5000000 1.0000000 0.3333333 1.0000000 1.0000000 0.7500000
|
||
|
|
man 0.8000000 0.6666667 0.4000000 0.8000000 0.0000000 0.2000000 0.5000000
|
||
|
|
rab 0.7500000 0.6000000 0.2500000 0.7500000 0.2000000 0.0000000 0.4000000
|
||
|
|
sal 0.3333333 0.7500000 0.6666667 0.6666667 0.7500000 0.6666667 0.5000000
|
||
|
|
spi 0.5000000 0.4000000 0.5000000 0.0000000 0.7500000 0.7500000 1.0000000
|
||
|
|
wha 0.6000000 0.8333333 0.6000000 1.0000000 0.2000000 0.4000000 0.3333333
|
||
|
|
eag ele fly fro her lio liz
|
||
|
|
bee
|
||
|
|
cat
|
||
|
|
cpl
|
||
|
|
chi
|
||
|
|
cow
|
||
|
|
duc
|
||
|
|
eag
|
||
|
|
ele 0.3333333
|
||
|
|
fly 0.5000000 0.8333333
|
||
|
|
fro 0.4000000 0.2500000 0.6000000
|
||
|
|
her 0.6666667 0.4000000 0.6000000 0.2500000
|
||
|
|
lio 0.6000000 0.2500000 1.0000000 0.6666667 0.5000000
|
||
|
|
liz 0.5000000 0.6000000 0.4000000 0.2500000 0.2500000 0.7500000
|
||
|
|
lob 0.8000000 0.7500000 0.2500000 0.5000000 0.3333333 1.0000000 0.3333333
|
||
|
|
man 0.5000000 0.2000000 1.0000000 0.5000000 0.6000000 0.0000000 0.8000000
|
||
|
|
rab 0.6666667 0.4000000 1.0000000 0.7500000 0.5000000 0.0000000 0.7500000
|
||
|
|
sal 0.6000000 0.5000000 0.5000000 0.2500000 0.0000000 0.6666667 0.0000000
|
||
|
|
spi 0.8000000 1.0000000 0.4000000 0.6666667 0.7500000 0.7500000 0.5000000
|
||
|
|
wha 0.3333333 0.0000000 0.8333333 0.2500000 0.4000000 0.2500000 0.6000000
|
||
|
|
lob man rab sal spi
|
||
|
|
bee
|
||
|
|
cat
|
||
|
|
cpl
|
||
|
|
chi
|
||
|
|
cow
|
||
|
|
duc
|
||
|
|
eag
|
||
|
|
ele
|
||
|
|
fly
|
||
|
|
fro
|
||
|
|
her
|
||
|
|
lio
|
||
|
|
liz
|
||
|
|
lob
|
||
|
|
man 1.0000000
|
||
|
|
rab 1.0000000 0.2000000
|
||
|
|
sal 0.3333333 0.7500000 0.6666667
|
||
|
|
spi 0.3333333 0.7500000 0.7500000 0.6666667
|
||
|
|
wha 0.7500000 0.2000000 0.4000000 0.5000000 1.0000000
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, A, S, A, S, S
|
||
|
|
Number of objects : 20
|
||
|
|
> stopifnot(c(d1) == c(d2))
|
||
|
|
>
|
||
|
|
> d3 <- daisy(2 - animals, type=list(asymm=c(2,4)))
|
||
|
|
Warning message:
|
||
|
|
In daisy(2 - animals, type = list(asymm = c(2, 4))) :
|
||
|
|
binary variable(s) 1, 3, 5, 6 treated as interval scaled
|
||
|
|
> (d4 <- daisy(2 - animals, type=list(symm = c(1,3,5,6), asymm=c(2,4))))
|
||
|
|
Dissimilarities :
|
||
|
|
ant bee cat cpl chi cow duc
|
||
|
|
bee 0.3333333
|
||
|
|
cat 0.6666667 0.6666667
|
||
|
|
cpl 0.3333333 0.3333333 0.3333333
|
||
|
|
chi 0.6666667 0.6666667 0.3333333 0.6666667
|
||
|
|
cow 0.5000000 0.5000000 0.1666667 0.5000000 0.1666667
|
||
|
|
duc 0.5000000 0.6000000 0.5000000 0.8333333 0.5000000 0.3333333
|
||
|
|
eag 0.8333333 1.0000000 0.5000000 0.8333333 0.6000000 0.6666667 0.4000000
|
||
|
|
ele 0.5000000 0.8333333 0.5000000 0.8333333 0.2000000 0.3333333 0.3333333
|
||
|
|
fly 0.3333333 0.4000000 0.6666667 0.3333333 1.0000000 0.8333333 0.6000000
|
||
|
|
fro 0.4000000 0.8000000 0.6000000 0.6000000 0.5000000 0.6000000 0.6000000
|
||
|
|
her 0.1666667 0.5000000 0.5000000 0.5000000 0.5000000 0.3333333 0.3333333
|
||
|
|
lio 0.6000000 0.6000000 0.2000000 0.6000000 0.0000000 0.0000000 0.4000000
|
||
|
|
liz 0.3333333 0.6666667 0.3333333 0.3333333 0.6666667 0.5000000 0.5000000
|
||
|
|
lob 0.0000000 0.4000000 0.6000000 0.2000000 0.8000000 0.6000000 0.6000000
|
||
|
|
man 0.6666667 0.6666667 0.3333333 0.6666667 0.0000000 0.1666667 0.5000000
|
||
|
|
rab 0.5000000 0.5000000 0.1666667 0.5000000 0.1666667 0.0000000 0.3333333
|
||
|
|
sal 0.2000000 0.6000000 0.4000000 0.4000000 0.6000000 0.4000000 0.4000000
|
||
|
|
spi 0.4000000 0.4000000 0.4000000 0.0000000 0.6000000 0.6000000 1.0000000
|
||
|
|
wha 0.5000000 0.8333333 0.5000000 0.8333333 0.2000000 0.3333333 0.3333333
|
||
|
|
eag ele fly fro her lio liz
|
||
|
|
bee
|
||
|
|
cat
|
||
|
|
cpl
|
||
|
|
chi
|
||
|
|
cow
|
||
|
|
duc
|
||
|
|
eag
|
||
|
|
ele 0.4000000
|
||
|
|
fly 0.6000000 0.8333333
|
||
|
|
fro 0.5000000 0.2500000 0.6000000
|
||
|
|
her 0.6666667 0.3333333 0.5000000 0.2000000
|
||
|
|
lio 0.6000000 0.2000000 1.0000000 0.5000000 0.4000000
|
||
|
|
liz 0.5000000 0.5000000 0.3333333 0.2000000 0.1666667 0.6000000
|
||
|
|
lob 0.8000000 0.6000000 0.2000000 0.4000000 0.2000000 0.7500000 0.2000000
|
||
|
|
man 0.6000000 0.2000000 1.0000000 0.5000000 0.5000000 0.0000000 0.6666667
|
||
|
|
rab 0.6666667 0.3333333 0.8333333 0.6000000 0.3333333 0.0000000 0.5000000
|
||
|
|
sal 0.6000000 0.4000000 0.4000000 0.2000000 0.0000000 0.5000000 0.0000000
|
||
|
|
spi 0.8000000 0.8000000 0.4000000 0.5000000 0.6000000 0.6000000 0.4000000
|
||
|
|
wha 0.4000000 0.0000000 0.8333333 0.2500000 0.3333333 0.2000000 0.5000000
|
||
|
|
lob man rab sal spi
|
||
|
|
bee
|
||
|
|
cat
|
||
|
|
cpl
|
||
|
|
chi
|
||
|
|
cow
|
||
|
|
duc
|
||
|
|
eag
|
||
|
|
ele
|
||
|
|
fly
|
||
|
|
fro
|
||
|
|
her
|
||
|
|
lio
|
||
|
|
liz
|
||
|
|
lob
|
||
|
|
man 0.8000000
|
||
|
|
rab 0.6000000 0.1666667
|
||
|
|
sal 0.2000000 0.6000000 0.4000000
|
||
|
|
spi 0.2500000 0.6000000 0.6000000 0.5000000
|
||
|
|
wha 0.6000000 0.2000000 0.3333333 0.4000000 0.8000000
|
||
|
|
|
||
|
|
Metric : mixed ; Types = S, A, S, A, S, S
|
||
|
|
Number of objects : 20
|
||
|
|
> stopifnot(c(d3) == c(d4))
|
||
|
|
>
|
||
|
|
> pairs(cbind(d0,d2,d4),
|
||
|
|
+ main = "Animals -- symmetric and asymm. dissimilarities")
|
||
|
|
>
|
||
|
|
> proc.time()
|
||
|
|
user system elapsed
|
||
|
|
0.518 0.113 0.905
|