| disc {ade4} | R Documentation |
Calculates the root square of Rao's dissimilarity coefficient between samples.
disc(samples, dis = NULL, structures = NULL)
samples |
a data frame with elements as rows, samples as columns, and abundance, presence-absence or frequencies as entries |
dis |
an object of class dist containing distances or dissimilarities among elements.
If dis is NULL, equidistances are used. |
structures |
a data frame containing, in the jth row and the kth column, the name of the group of level k to which the jth population belongs. |
Returns a list of objects of class dist
Sandrine Pavoine pavoine@biomserv.univ-lyon1.fr
Rao, C.R. (1982) Diversity and dissimilarity coefficients: a unified approach. Theoretical Population Biology, 21, 24–43.
data(humDNAm) humDNA.dist <- disc(humDNAm$samples, sqrt(humDNAm$distances), humDNAm$structures) humDNA.dist is.euclid(humDNA.dist$samples) is.euclid(humDNA.dist$regions) ## Not run: data(ecomor) dtaxo <- dist.taxo(ecomor$taxo) ecomor.dist <- disc(ecomor$habitat, dtaxo) ecomor.dist is.euclid(ecomor.dist) ## End(Not run)
> library(ade4)
> ### Name: disc
> ### Title: Rao's dissimilarity coefficient
> ### Aliases: disc
> ### Keywords: multivariate
>
> ### ** Examples
>
> data(humDNAm)
> humDNA.dist <- disc(humDNAm$samples, sqrt(humDNAm$distances), humDNAm$structures)
> humDNA.dist
$samples
oriental tharu wolof peul pima maya finnish
tharu 0.2520200
wolof 0.7821356 0.7965116
peul 0.8506600 0.8632233 0.1251814
pima 0.1994968 0.2755218 0.7582823 0.8338317
maya 0.2559697 0.3023221 0.7177691 0.7857762 0.1406173
finnish 0.2455583 0.3043545 0.7615230 0.8367302 0.1416780 0.1899101
sicilian 0.2966927 0.3553515 0.7194281 0.7871977 0.2731589 0.2783955 0.2593187
israelij 0.3578283 0.4564520 0.7963554 0.8604647 0.3906841 0.4075339 0.3601095
israelia 0.4102655 0.4363589 0.5822519 0.6437361 0.3588124 0.3027937 0.2984287
sicilian israelij
tharu
wolof
peul
pima
maya
finnish
sicilian
israelij 0.3690240
israelia 0.3541134 0.3947386
$regions
africa america asia europe
america 0.7609083
asia 0.8016371 0.2280650
europe 0.7519837 0.1646208 0.2553667
middleeast 0.6866876 0.3045622 0.3592600 0.2518122
> is.euclid(humDNA.dist$samples)
[1] TRUE
> is.euclid(humDNA.dist$regions)
[1] TRUE
>
> data(ecomor)
> dtaxo <- dist.taxo(ecomor$taxo)
> ecomor.dist <- disc(ecomor$habitat, dtaxo)
> ecomor.dist
Bu1 Bu2 Bu3 Bu4 Ca1 Ca2 Ca3
Bu2 0.2299347
Bu3 0.4445234 0.3141620
Bu4 0.4678652 0.3406236 0.1103982
Ca1 0.9502364 0.9410382 0.9761147 0.9754643
Ca2 0.7570846 0.6969114 0.6931755 0.6831109 0.7205767
Ca3 0.6664796 0.6062407 0.5893602 0.5770824 0.7687061 0.3344968
Ca4 0.6231089 0.5463245 0.5427678 0.5311937 0.8279776 0.4048608 0.2460627
Ch1 0.9154968 0.9333730 0.9795237 0.9785106 0.8164966 0.8320503 0.8348471
Ch2 0.7724173 0.7866902 0.8353195 0.8341313 0.7807075 0.7237678 0.7041788
Ch3 0.6682402 0.6073798 0.5940866 0.5796164 0.8740074 0.5520455 0.4842859
Ch4 0.6816037 0.6245146 0.6131992 0.5984060 0.8861820 0.6018651 0.5296545
Pr1 0.5692630 0.5863691 0.6962758 0.6975175 0.9797959 0.7686151 0.7109533
Pr2 0.4720870 0.4953128 0.6158982 0.6185896 0.9845749 0.7754069 0.7084175
Pr3 0.5972043 0.5302328 0.6142023 0.6197341 1.0441637 0.7817360 0.7264832
Pr4 0.4555487 0.3920131 0.4335007 0.4510596 1.0021244 0.7372591 0.6648311
Ca4 Ch1 Ch2 Ch3 Ch4 Pr1 Pr2
Bu2
Bu3
Bu4
Ca1
Ca2
Ca3
Ca4
Ch1 0.8527682
Ch2 0.7048089 0.4391326
Ch3 0.4436571 0.7750448 0.5833087
Ch4 0.4888328 0.8404589 0.6644347 0.2797579
Pr1 0.6813933 0.9626353 0.8320045 0.7281064 0.7490714
Pr2 0.6771308 0.9600879 0.8243429 0.7089583 0.7274218 0.2941609
Pr3 0.6882887 1.0540926 0.9216307 0.7288690 0.7562197 0.5206833 0.3897787
Pr4 0.6262953 0.9930445 0.8511342 0.6679306 0.6936998 0.5605830 0.4527776
Pr3
Bu2
Bu3
Bu4
Ca1
Ca2
Ca3
Ca4
Ch1
Ch2
Ch3
Ch4
Pr1
Pr2
Pr3
Pr4 0.4119615
> is.euclid(ecomor.dist)
[1] TRUE
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