Running ‘fpctests.R’ [18s/21s]
Running the tests in ‘tests/fpctests.R’ failed.
Complete output:
  > # This tests a few things that are not run in the examples.
  > 
  > library(fpc)
  > library(MASS)
  > library(diptest)
  > library(mclust)
  Package 'mclust' version 5.4
  Type 'citation("mclust")' for citing this R package in publications.
  > options(digits=3)
  > 
  > set.seed(4634)
  > face <- rFace(300,dMoNo=2,dNoEy=0,p=3)
  > grface <- as.integer(attr(face,"grouping"))
  > discrproj(face,grface, clnum=1, method="bc")$units
  [1] "Cluster indicator has more than 2 values"
          [,1]  [,2]     [,3]
  [1,]  0.1548 0.373  0.49246
  [2,] -0.1981 0.006 -0.00132
  [3,]  0.0482 0.498 -0.66288
  > discrproj(face,grface, clnum=1, method="anc")$units
          [,1]    [,2]    [,3]
  [1,] -1.3912 -0.3093  0.1093
  [2,]  0.6211 -0.2233  0.0164
  [3,] -0.0313  0.0749 -0.8074
  > discrproj(face,grface, clnum=1, method="awc")$units
         [,1]    [,2]     [,3]
  [1,]  0.215 -0.3389 -0.51886
  [2,] -0.370  0.0144 -0.00893
  [3,]  0.111  0.7914 -0.23574
  > 
  > 
  > pamk(face,krange=1:5,criterion="ch",usepam=FALSE,critout=TRUE)
  1  clusters  0 
  2  clusters  1321 
  3  clusters  963 
  4  clusters  833 
  5  clusters  934 
  $pamobject
  Call:	 clara(x = sdata, k = k) 
  Medoids:
        [,1]  [,2] [,3]
  [1,] 0.119  3.53 1.49
  [2,] 1.742 17.02 1.12
  Objective function:	 2.44
  Clustering vector: 	 int [1:300] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 ...
  Cluster sizes:	    	 202 98 
  Best sample:
   [1]   5  11  18  21  28  40  50  61  62  65  79  82  83  86  93  94 105 119 130
  [20] 160 172 180 182 194 195 202 206 208 217 223 230 231 239 248 250 256 259 261
  [39] 264 268 271 274 277 299
  
  Available components:
   [1] "sample"     "medoids"    "i.med"      "clustering" "objective" 
   [6] "clusinfo"   "diss"       "call"       "silinfo"    "data"      
  
  $nc
  [1] 2
  
  $crit
  [1]    0 1321  963  833  934
  
  > 
  > set.seed(20000)
  > face50 <- rFace(50,dMoNo=2,dNoEy=0,p=2)
  > pamk(dist(face50),krange=1:5,criterion="asw",critout=TRUE)
  1  clusters  0 
  2  clusters  0.742 
  3  clusters  0.748 
  4  clusters  0.581 
  5  clusters  0.544 
  $pamobject
  Medoids:
       ID       
  [1,] "22" "22"
  [2,] "34" "34"
  [3,] "49" "49"
  Clustering vector:
   1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 
   1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1  1 
  27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 
   1  1  1  1  1  1  2  2  2  2  2  2  2  2  2  2  2  2  2  2  3  2  3  3 
  Objective function:
  build  swap 
   2.14  2.09 
  
  Available components:
  [1] "medoids"    "id.med"     "clustering" "objective"  "isolation" 
  [6] "clusinfo"   "silinfo"    "diss"       "call"      
  
  $nc
  [1] 3
  
  $crit
  [1] 0.000 0.742 0.748 0.581 0.544
  
  > 
  > x <- c(1,2,3,6,6,7,8,120)
  > ff8 <- fixmahal(x)
  > summary(ff8)
    *  Mahalanobis Fixed Point Clusters  *
  
  Often a clear cluster in the data leads to several similar FPCs.
  The summary shows the representative FPCs of groups of similar FPCs.
  
  Method  fuzzy  was used.
  Number of representative FPCs:  1 
  
  FPCs with less than  4  points were skipped.
  FPCs with ratio of times found to number of points less than  0.1  were skipped.
  0  iteration runs led to  0  skipped clusters.
    Weight 1 for r^2<=  3.84  weight 0 for r^2>  7.88  
    Constant ca=  3.84  corresponding to alpha=  0.95 
  
   FPC  1 
    Times found (group members):  9 
    Ratio to size:  1.29 
    Mean:
  [1] 4.71
    Covariance matrix:
       [,1]
  [1,]  6.2
    Number of points (sum of weights):  7 
  
  Number of points (rounded weights) in intersection of representative FPCs
       [,1]
  [1,]    7
  >   # ...dataset a bit too small for the defaults...
  > ff9 <- fixmahal(x, mnc=3, startn=3)
  > summary(ff9)
    *  Mahalanobis Fixed Point Clusters  *
  
  Often a clear cluster in the data leads to several similar FPCs.
  The summary shows the representative FPCs of groups of similar FPCs.
  
  Method  fuzzy  was used.
  Number of representative FPCs:  3 
  
  FPCs with less than  3  points were skipped.
  FPCs with ratio of times found to number of points less than  0.1  were skipped.
  0  iteration runs led to  0  skipped clusters.
    Weight 1 for r^2<=  3.84  weight 0 for r^2>  7.88  
    Constant ca=  3.84  corresponding to alpha=  0.95 
  
   FPC  1 
    Times found (group members):  4 
    Ratio to size:  1.33 
    Mean:
  [1] 6.33
    Covariance matrix:
        [,1]
  [1,] 0.222
    Number of points (sum of weights):  3 
  
   FPC  2 
    Times found (group members):  3 
    Ratio to size:  1 
    Mean:
  [1] 2
    Covariance matrix:
        [,1]
  [1,] 0.667
    Number of points (sum of weights):  3 
  
   FPC  3 
    Times found (group members):  2 
    Ratio to size:  0.286 
    Mean:
  [1] 4.71
    Covariance matrix:
       [,1]
  [1,]  6.2
    Number of points (sum of weights):  7 
  
  Number of points (rounded weights) in intersection of representative FPCs
       [,1] [,2] [,3]
  [1,]    3    0    3
  [2,]    0    3    3
  [3,]    3    3    7
  > 
  > set.seed(776655)
  > v1 <- rnorm(100)
  > v2 <- rnorm(100)
  > d1 <- sample(1:5,100,replace=TRUE)
  > d2 <- sample(1:4,100,replace=TRUE)
  > ldata <- cbind(v1,v2,d1,d2)
  > fr <- flexmixedruns(ldata,
  +     continuous=2,discrete=2,simruns=1,initial.cluster=c(rep(1,5),rep(2,45),
  +                                         rep(3,50)),
  +                     control=list(minprior=0.1),
  +                     n.cluster=3,allout=FALSE)
  k=  3  new best fit found in run  1 
  k=  3  BIC=  1300 
  > print(fr$optsummary)
  
  Call:
  flexmix(formula = x ~ 1, k = k, cluster = initial.cluster, model = lcmixed(continuous = continuous, 
      discrete = discrete, ppdim = ppdim, diagonal = diagonal), 
      control = control)
  
         prior size post>0 ratio
  Comp.1 0.427   43     79 0.544
  Comp.2 0.273   25     64 0.391
  Comp.3 0.300   32     78 0.410
  
  'log Lik.' -569 (df=35)
  AIC: 1209   BIC: 1300 
  
  > 
  > dface <- dist(face50)
  > 
  > 
  > hclusttreeCBI(face50,minlevel=2,method="complete",scaling=TRUE)
  $result
  
  Call:
  hclust(d = dist(sdata), method = method)
  
  Cluster method   : complete 
  Distance         : euclidean 
  Number of objects: 50 
  
  
  $nc
  [1] 48
  
  $clusterlist
  $clusterlist[[1]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49]  TRUE  TRUE
  
  $clusterlist[[2]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[3]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[4]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[5]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[6]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[7]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[8]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37]  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[9]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[10]]
   [1] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[11]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[12]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[13]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [37]  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[14]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[15]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[16]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[17]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [37]  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[18]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[19]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[20]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[21]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [13]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[22]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[23]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE
  [37]  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[24]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[25]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[26]]
   [1] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[27]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE
  [37]  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[28]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[29]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[30]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[31]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[32]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[33]]
   [1]  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[34]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[35]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[36]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[37]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[38]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[39]]
   [1] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[40]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[41]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[42]]
   [1]  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[43]]
   [1] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[44]]
   [1]  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[45]]
   [1] FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[46]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [49]  TRUE  TRUE
  
  $clusterlist[[47]]
   [1]  TRUE  TRUE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [49] FALSE FALSE
  
  $clusterlist[[48]]
   [1] FALSE FALSE FALSE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [49]  TRUE  TRUE
  
  
  $partition
   [1] 1 1 1 2 1 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1
  [39] 1 1 1 2 2 2 2 2 2 1 2 2
  
  $clustermethod
  [1] "hclust, full tree"
  
  > 
  > disthclusttreeCBI(dface,minlevel=2,method="complete")
  $result
  
  Call:
  hclust(d = as.dist(dmatrix), method = method)
  
  Cluster method   : complete 
  Distance         : euclidean 
  Number of objects: 50 
  
  
  $nc
  [1] 48
  
  $clusterlist
  $clusterlist[[1]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49]  TRUE  TRUE
  
  $clusterlist[[2]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[3]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[4]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[5]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[6]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [37] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[7]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[8]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [37]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[9]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [13]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[10]]
   [1] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[11]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[12]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[13]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[14]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[15]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[16]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[17]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[18]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[19]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[20]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[21]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25] FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[22]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [37] FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[23]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[24]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25]  TRUE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[25]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE
  [37]  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[26]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25] FALSE FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[27]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE FALSE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[28]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [13]  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[29]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE FALSE
  [37]  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[30]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE  TRUE
  [37] FALSE  TRUE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[31]]
   [1] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [13]  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[32]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25] FALSE FALSE  TRUE  TRUE  TRUE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[33]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[34]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE
  [13] FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[35]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[36]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[37]]
   [1] FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[38]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[39]]
   [1]  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[40]]
   [1] FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[41]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[42]]
   [1] FALSE  TRUE FALSE  TRUE FALSE  TRUE  TRUE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[43]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[44]]
   [1]  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[45]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE
  [49]  TRUE  TRUE
  
  $clusterlist[[46]]
   [1]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[47]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE
  [49]  TRUE  TRUE
  
  $clusterlist[[48]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE
  [49]  TRUE  TRUE
  
  
  $partition
   [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2
  [39] 2 2 2 2 2 2 2 2 2 2 2 2
  
  $clustermethod
  [1] "hclust, full tree"
  
  > 
  > noisemclustCBI(face50,G=1:5,emModelNames="VVV",nnk=2)
  $result
  Bayesian Information Criterion (BIC):
     VVV
  1 -525
  2 -473
  3 -469
  4 -455
  5 -469
  
  Top 3 models based on the BIC criterion:
  VVV,4 VVV,5 VVV,3 
   -455  -469  -469 
  
  $nc
  [1] 5
  
  $nccl
  [1] 4
  
  $clusterlist
  $clusterlist[[1]]
   [1] FALSE  TRUE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE
  [13]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[2]]
   [1] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE
  [25]  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[3]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE
  [37]  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[4]]
   [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE
  [49] FALSE FALSE
  
  $clusterlist[[5]]
   [1]  TRUE FALSE  TRUE FALSE  TRUE FALSE FALSE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE
  [49]  TRUE  TRUE
  
  
  $partition
   [1] 5 1 5 1 5 2 2 5 5 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3
  [39] 3 3 3 4 4 4 4 4 5 5 5 5
  
  $nnk
  [1] 2
  
  $initnoise
   [1]  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE
  [49]  TRUE  TRUE
  
  $clustermethod
  [1] "mclustBIC"
  
  > 
  > distnoisemclustCBI(dface,G=5,emModelNames="EEE",nnk=2,
  +                         mdsmethod="classical",
  +                         mdsdim=2)
  $result
  Bayesian Information Criterion (BIC):
     EEE
  5 -500
  
  Top 3 models based on the BIC criterion:
  EEE,5 
   -500 
  
  $nc
  [1] 6
  
  $nccl
  [1] 5
  
  $clusterlist
  $clusterlist[[1]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
  FALSE FALSE FALSE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE FALSE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
   TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     40    41    42    43    44    45    46    47    48    49    50 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
  
  $clusterlist[[2]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
  FALSE FALSE FALSE FALSE FALSE  TRUE FALSE FALSE FALSE  TRUE  TRUE FALSE  TRUE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
  FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
   TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     40    41    42    43    44    45    46    47    48    49    50 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
  
  $clusterlist[[3]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
  FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE 
     40    41    42    43    44    45    46    47    48    49    50 
   TRUE  TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
  
  $clusterlist[[4]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE 
     40    41    42    43    44    45    46    47    48    49    50 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
  
  $clusterlist[[5]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     40    41    42    43    44    45    46    47    48    49    50 
  FALSE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE 
  
  $clusterlist[[6]]
      1     2     3     4     5     6     7     8     9    10    11    12    13 
   TRUE  TRUE  TRUE FALSE  TRUE FALSE  TRUE  TRUE  TRUE FALSE FALSE FALSE FALSE 
     14    15    16    17    18    19    20    21    22    23    24    25    26 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     27    28    29    30    31    32    33    34    35    36    37    38    39 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE 
     40    41    42    43    44    45    46    47    48    49    50 
  FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE  TRUE  TRUE 
  
  
  $partition
   1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 
   6  6  6  1  6  2  6  6  6  2  2  1  2  1  2  2  2  2  2  2  2  2  2  2  2  2 
  27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 
   2  2  2  2  2  2  3  3  3  3  3  3  4  3  3  5  5  5  5  5  6  6  6  6 
  
  $nnk
  [1] 2
  
  $initnoise
   [1]  TRUE  TRUE  TRUE FALSE  TRUE  TRUE  TRUE  TRUE  TRUE FALSE FALSE FALSE
  [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [25] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
  [37] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE  TRUE  TRUE
  [49]  TRUE  TRUE
  
  $clustermethod
  [1] "mclustBIC"
  
  > 
  > mahalCBI(face50,clustercut=0.5)
  $result
  Mahalanobis Fixed Point Cluster object
  3  representative stable fixed point clusters
   of totally  7  found fixed point clusters.
  
  $nc
  [1] 3
  
  $clusterlist
  $clusterlist[[1]]
   [1] 0 0 0 1 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 1 1 0 0 0 1 1 0 0 0 0 0 0 0
  [39] 0 0 0 0 0 0 0 0 0 0 0 0
  
  $clusterlist[[2]]
   [1] 0 0 0 0 0 1 1 0 0 1 1 1 1 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0
  [39] 0 0 0 0 0 0 0 0 0 0 0 0
  
  $clusterlist[[3]]
   [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
  [39] 1 1 1 1 1 1 1 1 0 0 0 0
  
  
  $partition
   [1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
  [39] 1 1 1 1 1 1 1 1 1 1 1 1
  
  $clustermethod
  [1] "fixmahal"
  
  > 
  > set.seed(20000)
  > face100 <- rFace(100,dMoNo=2,dNoEy=0,p=2)
  > print(clusterboot(face100,B=2,clustermethod=speccCBI,showplots=TRUE,k=6,seed=50000))
  boot 1 
  boot 2 
  * Cluster stability assessment *
  Cluster method:  spectral 
  Full clustering results are given as parameter result
  of the clusterboot object, which also provides further statistics
  of the resampling results.
  Number of resampling runs:  2 
  
  Number of clusters found in data:  6 
  
   Clusterwise Jaccard bootstrap (omitting multiple points) mean:
  [1] 0.403 0.750 1.000 0.417 0.825 1.000
  dissolved:
  [1] 2 1 0 2 0 0
  recovered:
  [1] 0 1 2 0 1 2
  > # suppressWarnings(if(require(tclust))
  > # print(clusterboot(face100,B=2,clustermethod=tclustCBI,showplots=TRUE,k=5,seed=50000,noisemethod=TRUE)))
  > 
  > 
  > complete3 <- cutree(hclust(dface),3)
  > 
  > cluster.stats(dface,complete3,G2=TRUE)
  $n
  [1] 50
  
  $cluster.number
  [1] 3
  
  $cluster.size
  [1] 32 14  4
  
  $min.cluster.size
  [1] 4
  
  $noisen
  [1] 0
  
  $diameter
  [1] 8.53 4.94 9.00
  
  $average.distance
  [1] 2.95 2.15 7.05
  
  $median.distance
  [1] 2.94 1.44 8.32
  
  $separation
  [1] 8.67 7.46 7.46
  
  $average.toother
  [1] 15.5 12.9 20.6
  
  $separation.matrix
        [,1] [,2]  [,3]
  [1,]  0.00 8.67 17.24
  [2,]  8.67 0.00  7.46
  [3,] 17.24 7.46  0.00
  
  $ave.between.matrix
       [,1] [,2] [,3]
  [1,]  0.0   13 24.4
  [2,] 13.0    0 12.0
  [3,] 24.4   12  0.0
  
  $average.between
  [1] 15.2
  
  $average.within
  [1] 2.87
  
  $n.between
  [1] 632
  
  $n.within
  [1] 593
  
  $max.diameter
  [1] 9
  
  $min.separation
  [1] 7.46
  
  $within.cluster.ss
  [1] 319
  
  $clus.avg.silwidths
      1     2     3 
  0.764 0.821 0.346 
  
  $avg.silwidth
  [1] 0.746
  
  $g2
  [1] 1
  
  $g3
  NULL
  
  $pearsongamma
  [1] 0.838
  
  $dunn
  [1] 0.829
  
  $dunn2
  [1] 1.71
  
  $entropy
  [1] 0.844
  
  $wb.ratio
  [1] 0.188
  
  $ch
  [1] 229
  
  $cwidegap
  [1] 2.90 2.49 8.32
  
  $widestgap
  [1] 8.32
  
  $sindex
  [1] 7.78
  
  $corrected.rand
  NULL
  
  $vi
  NULL
  
  > 
  > set.seed(55667788)
  > 
  > data(crabs)
  > dc <- crabs[,4:8]
  > cmo <- mclustBIC(crabs[,4:8],G=9,modelNames="EEE")
  > # set.seed(12345)
  > cm <- mclustBIC(crabs[,4:8],G=9,modelNames="EEE",
  +                 initialization=list(noise=(1:200)[sample(200,50)]))
  > 
  > 
  > scm <- summary(cm,crabs[,4:8])
  > scmo <- summary(cmo,crabs[,4:8])
  > 
  > set.seed(334455)
  > summary(mergenormals(crabs[,4:8],scm,method="ridge.ratio",by=0.05))
  * Merging Gaussian mixture components *
  
   Method:  ridge.ratio , cutoff value:  0.2 
   Original number of components:  9 
     (not including noise which is denoted by clustering=0)
   Number of clusters after merging:  1 
   Values at which clusters were merged: 
       [,1]  [,2]
  [1,]    8 0.804
  [2,]    7 1.000
  [3,]    6 1.000
  [4,]    5 1.000
  [5,]    4 0.881
  [6,]    3 0.948
  [7,]    2 0.739
  [8,]    1 0.700
   Components assigned to clusters: 
        [,1]
   [1,]    0
   [2,]    1
   [3,]    1
   [4,]    1
   [5,]    1
   [6,]    1
   [7,]    1
   [8,]    1
   [9,]    1
  [10,]    1
  > summary(mergenormals(crabs[,4:8],scmo,method="ridge.uni",by=0.05))
  * Merging Gaussian mixture components *
  
   Method:  ridge.uni , cutoff value:  1 
   Original number of components:  9 
   Number of clusters after merging:  8 
   Values at which clusters were merged: 
       [,1]
  [1,]    8
  [2,]    9
   Components assigned to clusters: 
        [,1]
   [1,]    1
   [2,]    1
   [3,]    2
   [4,]    3
   [5,]    4
   [6,]    5
   [7,]    6
   [8,]    7
   [9,]    8
  > # summary(mergenormals(crabs[,4:8],scm,method="diptantrum",by=0.05))
  > # summary(mergenormals(crabs[,4:8],scmo,method="dipuni",by=0.05))
  > summary(mergenormals(crabs[,4:8],scm,method="predictive",M=2))
  * Merging Gaussian mixture components *
  
   Method:  predictive , cutoff value:  0.75 
   Original number of components:  9 
     (not including noise which is denoted by clustering=0)
   Number of clusters after merging:  1 
   Predictive strength values: 
         [,1]
   [1,] 1.000
   [2,] 0.570
   [3,] 0.503
   [4,] 0.413
   [5,] 0.359
   [6,] 0.387
   [7,] 0.380
   [8,] 0.366
   [9,] 0.325
   Components assigned to clusters: 
        [,1]
   [1,]    0
   [2,]    1
   [3,]    1
   [4,]    1
   [5,]    1
   [6,]    1
   [7,]    1
   [8,]    1
   [9,]    1
  [10,]    1
  > 
  > set.seed(20000)
  > x1 <- rnorm(50)
  > y <- rnorm(100)
  > x2 <- rnorm(40,mean=20)
  > x3 <- rnorm(10,mean=25,sd=100)
  > x0 <- cbind(c(x1,x2,x3),y)
  > 
  > prediction.strength(x0,M=10,Gmax=4,
  +                            clustermethod=noisemclustCBI,
  +                            classification="qda")
  Error in `[.default`(ctable, kk, ) : subscript out of bounds
  Calls: prediction.strength -> [ -> [.table -> NextMethod
  Execution halted