In an object of type `Contsimulation`

data can be simulated in any distribution and size. One part
(usually the largest) of the random numbers stems from an ideal distribution, the rest from a contaminating distribution.

Objects can be created by calls of the form ```
Contsimulation(filename, samplesize, runs, seed, distribution.id,
distribution.c, rate)
```

(observation dimension is deduced from slot `distribution.id`

).
A `Contsimulation`

-object includes a filename, the number of runs, the size of the sample, the seed, the distribution
of the ideal and the contaminated data and the contamination rate. The slot Data stays empty until the method simulate has
been used. The same goes for slots Data.id and Data.c.

`ind`

:Object of class

`"MatrixorNULLorVector"`

: Indicator of the same length as the data; saves whether each element of the data vector is contaminated or not`Data.id`

:Object of class

`"ArrayorNULLorVector"`

: – the ideal data`Data.c`

:Object of class

`"ArrayorNULLorVector"`

: – the contaminated data`rate`

:Object of class

`"numeric"`

: the contamination rate, so the probability for each random number to be contaminated`distribution.c`

:Object of class

`"UnivariateDistribution"`

: the distribution of the ideal data`distribution.id`

:Object of class

`"UnivariateDistribution"`

: the distribution of the contaminated data`seed`

:Object of class

`"list"`

: the seed the simulation has been generated with`name`

:Object of class

`"character"`

: a name for the Contsimulation`filename`

:Object of class

`"character"`

: the filename the Contsimulation shall be saved`Data`

:Object of class

`"ArrayorNULLorVector"`

: the simulated data`samplesize`

:Object of class

`"numeric"`

: the size of the sample, so the dimension of the data`obsDim`

:Object of class

`"numeric"`

: the observation dimension of the data`runs`

:Object of class

`"numeric"`

: the number of runs of the data

Class `"Dataclass"`

, directly.

- Data.c
`signature(object = "Contsimulation")`

: returns the contaminated data- Data.id
`signature(object = "Contsimulation")`

: returns the ideal data- Data<-
`signature(object = "Contsimulation")`

: ERROR: A modification of simulated data is not allowed.- filename
`signature(object = "Contsimulation")`

: returns the the filename- filename<-
`signature(object = "Contsimulation")`

: changes the the filename- name
`signature(object = "Contsimulation")`

: returns the the name- name<-
`signature(object = "Contsimulation")`

: changes the the name- distribution.c
`signature(object = "Contsimulation")`

: returns the distribution of the contaminated data- distribution.c<-
`signature(object = "Contsimulation")`

: changes the distribution of the contaminated data- distribution.id
`signature(object = "Contsimulation")`

: returns the distribution of the ideal data- distribution.id<-
`signature(object = "Contsimulation")`

: changes the distribution of the ideal data- seed
`signature(object = "Contsimulation")`

: returns the seed- seed<-
`signature(object = "Contsimulation")`

: changes the seed- ind
`signature(object = "Contsimulation")`

: returns the indicator which saves which data is contaminated- initialize
`signature(.Object = "Contsimulation")`

: initialize method- rate
`signature(object = "Contsimulation")`

: returns the contamination rate- rate<-
`signature(object = "Contsimulation")`

: changes the contamination rate- obsDim
`signature(object = "Contsimulation")`

: returns the dimension of the observations- getVersion
`signature(object = "Contsimulation")`

: returns the version of this package, under which this object was generated- runs
`signature(object = "Contsimulation")`

: returns the number of runs- runs<-
`signature(object = "Contsimulation")`

: changes the number of runs- samplesize
`signature(object = "Contsimulation")`

: returns the size of the sample- samplesize<-
`signature(object = "Contsimulation")`

: changes the size of the sample- savedata
`signature(object = "Contsimulation")`

: saves the object without the data in the directory of R. (After loading the data can be reproduced by using simulate.)- simulate
`signature(x = "Contsimulation")`

: generates the random numbers for the simulation- plot
`signature(x = "Contsimulation")`

: produces a plot of the real data matrix; ; for details confer`plot-methods`

`signature(x = "Contsimulation")`

: returns filename, seed, the observation dimension, the number of runs, the size of the sample, the contamination rate and the distributions, and, if from a version > 1.8, also the package version under which the object was generated- summary
`signature(object = "Contsimulation")`

: returns filename, seed, number of runs, the size of the sample, the rate and a statistical summary for each run of the real data

Changing distributions, seed, runs, samplesize or rate deletes possibly simulated data, as it would not fit to the new parameters.

Thomas Stabla statho3@web.de,

Florian Camphausen fcampi@gmx.de,

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,

Matthias Kohl Matthias.Kohl@stamats.de

`Dataclass-class`

`Simulation-class`

`savedata-methods`

`plot-methods`

`simulate-methods`

`summary-methods`

`getVersion-methods`

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ```
N <- Norm() # N is a standard normal distribution.
C <- Cauchy() # C is a Cauchy distribution
cs <- Contsimulation(filename = "csim",
runs = 10,
samplesize = 3,
seed = setRNG(),
distribution.id = N,
distribution.c = C,
rate = 0.1)
simulate(cs)
# Each of the 30 random numbers is ideal (N-distributed) with
# probability 0.9 and contaminated (C-distributed) with
# probability = 0.1
Data(cs)
Data.id(cs)
Data.c(cs)
ind(cs)
summary(cs)
Data(cs) # different data
savedata(cs) # saves the object in the working directory of R...
load("csim") # loads it again...
Data(cs) # ...without the data - use simulate to return it!
``` |

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