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> ## VT::15.09.2013 - this will render the output independent
> ##  from the version of the package
> suppressPackageStartupMessages(library(rrcov))
> 
> ## VT::14.01.2020
> ##  On some platforms minor differences are shown - use
>         ## IGNORE_RDIFF_BEGIN
>         ## IGNORE_RDIFF_END
> 
> dodata <- function(nrep=1, time=FALSE, short=FALSE, full=TRUE, method = c("FASTMCD","MASS")){
+     domcd <- function(x, xname, nrep=1){
+         n <- dim(x)[1]
+         p <- dim(x)[2]
+ 
+         mcd<-CovOgk(x)
+ 
+         xres <- sprintf("%3d %3d\n", dim(x)[1], dim(x)[2])
+ 
+         lpad<-lname-nchar(xname)
+         cat(pad.right(xname,lpad), xres)
+ 
+         dist <- getDistance(mcd)
+         quantiel <- qchisq(0.975, p)
+         ibad <- which(dist >= quantiel)
+         names(ibad) <- NULL
+         nbad <- length(ibad)
+         cat("Outliers: ",nbad,"\n")
+         if(nbad > 0)
+             print(ibad)
+         cat("-------------\n")
+         show(mcd)
+         cat("--------------------------------------------------------\n")
+     }
+ 
+     lname <- 20
+ 
+     ## VT::15.09.2013 - this will render the output independent
+     ##  from the version of the package
+     suppressPackageStartupMessages(library(rrcov))
+ 
+     method <- match.arg(method)
+ 
+     data(heart)
+     data(starsCYG)
+     data(phosphor)
+     data(stackloss)
+     data(coleman)
+     data(salinity)
+     data(wood)
+ 
+     data(hbk)
+ 
+     data(Animals, package = "MASS")
+     brain <- Animals[c(1:24, 26:25, 27:28),]
+     data(milk)
+     data(bushfire)
+ 
+     tmp <- sys.call()
+     cat("\nCall: ", deparse(substitute(tmp)),"\n")
+ 
+     cat("Data Set               n   p  Half LOG(obj)        Time\n")
+     cat("========================================================\n")
+     domcd(heart[, 1:2], data(heart), nrep)
+ ## This will not work within the function, of course
+ ##  - comment it out
+ ## IGNORE_RDIFF_BEGIN
+ ##    domcd(starsCYG,data(starsCYG), nrep)
+ ## IGNORE_RDIFF_END
+     domcd(data.matrix(subset(phosphor, select = -plant)), data(phosphor), nrep)
+     domcd(stack.x,data(stackloss), nrep)
+     domcd(data.matrix(subset(coleman, select = -Y)), data(coleman), nrep)
+     domcd(data.matrix(subset(salinity, select = -Y)), data(salinity), nrep)
+ ## IGNORE_RDIFF_BEGIN
+ ##    domcd(data.matrix(subset(wood, select = -y)), data(wood), nrep)
+ ## IGNORE_RDIFF_END
+     domcd(data.matrix(subset(hbk,  select = -Y)), data(hbk), nrep)
+ 
+     domcd(brain, "Animals", nrep)
+     domcd(milk, data(milk), nrep)
+     domcd(bushfire, data(bushfire), nrep)
+     cat("========================================================\n")
+ }
> 
> pad.right <- function(z, pads)
+ {
+ ### Pads spaces to right of text
+     padding <- paste(rep(" ", pads), collapse = "")
+     paste(z, padding, sep = "")
+ }
> 
> dodata()

Call:  dodata() 
Data Set               n   p  Half LOG(obj)        Time
========================================================
heart                 12   2
Outliers:  5 
[1]  2  6  8 10 12
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
height  weight  
 39.76   35.71  

Robust Estimate of Covariance: 
        height  weight
height  15.88   32.07 
weight  32.07   78.28 
--------------------------------------------------------
phosphor              18   2
Outliers:  2 
[1] 1 6
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
  inorg  organic  
  13.31    40.00  

Robust Estimate of Covariance: 
         inorg   organic
inorg     92.82   93.24 
organic   93.24  152.62 
--------------------------------------------------------
stackloss             21   3
Outliers:  2 
[1] 1 2
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
  Air.Flow  Water.Temp  Acid.Conc.  
     57.72       20.50       85.78  

Robust Estimate of Covariance: 
            Air.Flow  Water.Temp  Acid.Conc.
Air.Flow    38.423    11.306      18.605    
Water.Temp  11.306     6.806       5.889    
Acid.Conc.  18.605     5.889      29.840    
--------------------------------------------------------
coleman               20   5
Outliers:  3 
[1]  1  6 10
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
  salaryP   fatherWc    sstatus  teacherSc  motherLev  
    2.723     43.202      2.912     25.010      6.290  

Robust Estimate of Covariance: 
           salaryP    fatherWc   sstatus    teacherSc  motherLev
salaryP      0.12867    2.80048    0.92026    0.15118    0.06413
fatherWc     2.80048  678.72549  227.36415    9.30826   16.15102
sstatus      0.92026  227.36415  101.39094    3.38013    5.63283
teacherSc    0.15118    9.30826    3.38013    0.57112    0.27701
motherLev    0.06413   16.15102    5.63283    0.27701    0.44801
--------------------------------------------------------
salinity              28   3
Outliers:  3 
[1]  3  5 16
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
   X1     X2     X3  
10.74   2.68  22.99  

Robust Estimate of Covariance: 
    X1       X2       X3     
X1   8.1047  -0.6365  -0.4720
X2  -0.6365   3.0976  -1.3520
X3  -0.4720  -1.3520   2.3648
--------------------------------------------------------
hbk                   75   3
Outliers:  14 
 [1]  1  2  3  4  5  6  7  8  9 10 11 12 13 14
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
   X1     X2     X3  
1.538  1.780  1.687  

Robust Estimate of Covariance: 
    X1       X2       X3     
X1  1.11350  0.04992  0.11541
X2  0.04992  1.13338  0.13843
X3  0.11541  0.13843  1.05261
--------------------------------------------------------
Animals               28   2
Outliers:  12 
 [1]  2  6  7  9 12 14 15 16 17 24 25 28
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
  body   brain  
 39.65  105.83  

Robust Estimate of Covariance: 
       body   brain
body    3981   7558
brain   7558  16594
--------------------------------------------------------
milk                  86   8
Outliers:  22 
 [1]  1  2  3 11 12 13 14 15 16 17 18 20 27 41 44 47 50 70 74 75 77 85
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
    X1      X2      X3      X4      X5      X6      X7      X8  
  1.03   35.80   33.10   26.15   25.13   25.06  123.06   14.39  

Robust Estimate of Covariance: 
    X1         X2         X3         X4         X5         X6         X7       
X1  4.074e-07  5.255e-05  1.564e-04  1.506e-04  1.340e-04  1.234e-04  5.308e-04
X2  5.255e-05  1.464e+00  3.425e-01  2.465e-01  1.847e-01  2.484e-01  1.459e+00
X3  1.564e-04  3.425e-01  1.070e+00  7.834e-01  7.665e-01  7.808e-01  7.632e-01
X4  1.506e-04  2.465e-01  7.834e-01  6.178e-01  5.868e-01  5.959e-01  5.923e-01
X5  1.340e-04  1.847e-01  7.665e-01  5.868e-01  6.124e-01  5.967e-01  5.868e-01
X6  1.234e-04  2.484e-01  7.808e-01  5.959e-01  5.967e-01  6.253e-01  5.819e-01
X7  5.308e-04  1.459e+00  7.632e-01  5.923e-01  5.868e-01  5.819e-01  3.535e+00
X8  1.990e-07  1.851e-01  1.861e-01  1.210e-01  1.041e-01  1.116e-01  3.046e-01
    X8       
X1  1.990e-07
X2  1.851e-01
X3  1.861e-01
X4  1.210e-01
X5  1.041e-01
X6  1.116e-01
X7  3.046e-01
X8  1.292e-01
--------------------------------------------------------
bushfire              38   5
Outliers:  17 
 [1]  7  8  9 10 11 12 28 29 30 31 32 33 34 35 36 37 38
-------------

Call:
CovOgk(x = x)
-> Method:  Orthogonalized Gnanadesikan-Kettenring Estimator 

Robust Estimate of Location: 
   V1     V2     V3     V4     V5  
104.5  146.0  275.6  217.8  279.3  

Robust Estimate of Covariance: 
    V1       V2       V3       V4       V5     
V1    266.8    203.2  -1380.7   -311.1   -252.2
V2    203.2    178.4   -910.9   -185.9   -155.9
V3  -1380.7   -910.9   8279.7   2035.5   1615.4
V4   -311.1   -185.9   2035.5    536.5    418.6
V5   -252.2   -155.9   1615.4    418.6    329.2
--------------------------------------------------------
========================================================
> 
> proc.time()
   user  system elapsed 
   0.48    0.07    0.56