silhouette_criterion {admix} R Documentation

## Compute the silhouette criterion related to the K populations that were clustered

### Description

Compute the silhouette criterion in k-sample clustering of admixture models.

### Usage

```silhouette_criterion(clusters_obj)
```

### Arguments

 `clusters_obj` an object obtained from function 'k_samples_clustering'.

### Value

the silhouette criterion computed for each of the K populations under study.

### Author(s)

Xavier Milhaud xavier.milhaud.research@gmail.com

### Examples

```
###### Case study with 5 populations to cluster on R+ with Gamma-Exponential mixtures.
## Simulate data (chosen parameters indicate 3 clusters (populations (1,3), (2,5) and 4)!):
list.comp <- list(f1 = "gamma", g1 = "exp",
f2 = "gamma", g2 = "exp",
f3 = "gamma", g3 = "gamma",
f4 = "exp", g4 = "exp",
f5 = "gamma", g5 = "exp")
list.param <- list(f1 = list(shape = 16, rate = 4), g1 = list(rate = 1/3.5),
f2 = list(shape = 14, rate = 2), g2 = list(rate = 1/5),
f3 = list(shape = 16, rate = 4), g3 = list(shape = 12, rate = 2),
f4 = list(rate = 1/2), g4 = list(rate = 1/7),
f5 = list(shape = 14, rate = 2), g5 = list(rate = 1/6))
A.sim <- rsimmix(n=8000, unknownComp_weight=0.7, comp.dist = list(list.comp\$f1,list.comp\$g1),
comp.param = list(list.param\$f1, list.param\$g1))\$mixt.data
B.sim <- rsimmix(n=8000, unknownComp_weight=0.6, comp.dist = list(list.comp\$f2,list.comp\$g2),
comp.param = list(list.param\$f2, list.param\$g2))\$mixt.data
C.sim <- rsimmix(n=8000, unknownComp_weight=0.5, comp.dist = list(list.comp\$f3,list.comp\$g3),
comp.param = list(list.param\$f3, list.param\$g3))\$mixt.data
D.sim <- rsimmix(n=8000, unknownComp_weight=0.4, comp.dist = list(list.comp\$f4,list.comp\$g4),
comp.param = list(list.param\$f4, list.param\$g4))\$mixt.data
E.sim <- rsimmix(n=8000, unknownComp_weight=0.3, comp.dist = list(list.comp\$f5,list.comp\$g5),
comp.param = list(list.param\$f5, list.param\$g5))\$mixt.data
## Look for the clusters:
list.comp <- list(f1 = NULL, g1 = "exp",
f2 = NULL, g2 = "exp",
f3 = NULL, g3 = "gamma",
f4 = NULL, g4 = "exp",
f5 = NULL, g5 = "exp")
list.param <- list(f1 = NULL, g1 = list(rate = 1/3.5),
f2 = NULL, g2 = list(rate = 1/5),
f3 = NULL, g3 = list(shape = 12, rate = 2),
f4 = NULL, g4 = list(rate = 1/7),
f5 = NULL, g5 = list(rate = 1/6))
clusters <- admix_clustering(samples = list(A.sim,B.sim,C.sim,D.sim,E.sim), n_sim_tab = 8,
comp.dist = list.comp, comp.param = list.param, parallel = FALSE, n_cpu = 2)
clusters
silhouette_criterion(clusters_obj = clusters)

```

[Package admix version 0.3.2 Index]