distrSim – S4-classes for Simulations Based on Package distr

Description

distrSim is to provide a conceptual treatment of simulations by means of S4 classes. The package is based on our package distr, hence uses distribution classes as introduced there to describe the distributions under which simulations are performed.

Details

Classes

"SeqDataFrame"
      slots: data(list[of dataframes with common column structure])
"Dataclass"
      slots: [<name>(<class>)] 
      filename(vectororNULL), 
      name(character), 
      Data(ArrayorNULLorVectororDataframeorSeqDataFrames), 
      runs(numeric), 
      samplesize(numeric),
      obsDim(numeric)      
|>"Simulation"
      (additional) slots: [<name>(<class>)] 
      seed(list), distribution(Distribution)
|>"Contsimulation"
      (additional) slots: [<name>(<class>)] 
      seed(list), ind(vectororNULL), rate(numeric),
      distribution.id(Distribution),
      distribution.c(Distribution),
      Data.id(vectororNULL),
      Data.c(vectororNULL)

Methods

savedata                Methods to save the data slot 
                       (for Simulation/Contsimulation)
simulate                Methods to fill the data slot 
                       (for Simulation/Contsimulation)
plot-methods            Methods for Function plot
                       (for Simulation/Contsimulation)
print-, show-methods    Methods for Function print/show 
                       (for Simulation/Contsimulation)
summary-methods         Methods for Function summary 
                       (for Simulation/Contsimulation)

Functions

cload                   loads just the comment slot 
                       (for Simulation/Contsimulation)

Slot accessors / -replacement functions

All slots are inspected / modified by corresponding accessors / -replacement functions, e.g. rate(X) for an object of class "Contsimulation".

Start-up-Banner

You may suppress the start-up banner/message completely by setting options("StartupBanner"="off") somewhere before loading this package by library or require in your R-code / R-session. If option "StartupBanner" is not defined (default) or setting options("StartupBanner"=NULL) or options("StartupBanner"="complete") the complete start-up banner is displayed. For any other value of option "StartupBanner" (i.e., not in c(NULL,"off","complete")) only the version information is displayed. The same can be achieved by wrapping the library or require call into either suppressStartupMessages() or onlytypeStartupMessages(.,atypes="version").

Far-reaching Change in Design

From version 1.8 of this package on, we have changed the format how data / simulations are stored: In order to be able to cope with multivariate distributions, regression distributions and (later) time series distributions, we have switched to the common array format: samplesize x obsDim x runs; you may check the version under which an object was generated by getVersion; for saved objects from earlier versions, we provide the functions isOldVersion, and conv2NewVersion-methods to check whether the object was generated by an older version of this package and to convert such an object to the new format, respectively.

Start-up-Banner

You may suppress the start-up banner/message completely by setting options("StartupBanner"="off") somewhere before loading this package by library or require in your R-code / R-session. If option "StartupBanner" is not defined (default) or setting options("StartupBanner"=NULL) or options("StartupBanner"="complete") the complete start-up banner is displayed. For any other value of option "StartupBanner" (i.e., not in c(NULL,"off","complete")) only the version information is displayed. As for general packageStartupMessage's, you may also suppress all the start-up banner by wrapping the library or require call into suppressPackageStartupMessages() from startupmsg-version 0.5 on.

Package versions

Note: The first two numbers of package versions do not necessarily reflect package-individual development, but rather are chosen for the distrXXX family as a whole in order to ease updating "depends" information.

Note

Global options controlling the plots and summaries of Dataclass and Simulation/Contsimulation objects may be inspected / set by distrSimoptions() and getdistrSimOption().

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de
Maintainer: Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de

References

P. Ruckdeschel, M. Kohl, T. Stabla, F. Camphausen (2006): S4 Classes for Distributions, R News, 6(2), 2-6. https://CRAN.R-project.org/doc/Rnews/Rnews_2006-2.pdf A vignette for packages distr, distrSim, distrTEst, and distrEx is included into the mere documentation package distrDoc and may be called by require("distrDoc");vignette("distr"). A homepage to this package is available under
https://distr.r-forge.r-project.org/

See Also

distr-package setRNG

Class "Contsimulation"

Description

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 from the Class

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.

Slots

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

Extends

Class "Dataclass", directly.

Methods

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

print

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

Note

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

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

Dataclass-class Simulation-class savedata-methods plot-methods simulate-methods summary-methods getVersion-methods

Examples

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!
## clean up
unlink("csim")

Methods for Function Data in Package ‘distrSim’

Description

Methods to access and change the Data-slot

Methods

Data

signature(object = "Dataclass"): returns the data

Data<-

signature(object = "Dataclass"): changes the data (does not work with a simulation or a contsimulation object)

Data<-

signature(object = "Simulation"): ERROR: A change of the data is not allowed.

Data<-

signature(object = "Contsimulation"): ERROR: A change of the data is not allowed.

Methods for Function Data.c in Package ‘distrSim’

Description

Data.c-methods

Methods

Data.c

signature(object = "Dataclass"): returns the contaminated data

Methods for Function Data.id in Package ‘distrSim’

Description

Data.id-methods

Methods

Data.id

signature(object = "Contsimulation"): returns the ideal data

Generating function for "Dataclass"

Description

Generates an object of class "Dataclass".

Usage

Dataclass(Data, ...)
## S4 method for signature 'ArrayorNULLorVector'
Dataclass(Data, filename = NULL, name = "Data-Set")
## S4 method for signature 'array'
Dataclass(Data, filename = NULL, name = "Data-Set")
## S4 method for signature 'matrix'
Dataclass(Data, filename = NULL, name = "Data-Set")
## S4 method for signature 'DataframeorSeqDataFrames'
Dataclass(Data, filename = NULL, name = "Data-Set")

Arguments

Author(s)

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

See Also

Dataclass-class

Class "Dataclass"

Description

In an object of type "Dataclass" data can be saved containing any number of runs in any dimension. All information about the data is stored in a unified way.

Objects from the Class

Objects can be created by calls to the generating function, method Dataclass(Data, filename = "Data-set", name = "Data-Set"). A Dataclass-object includes, aside from the actual data, a filename and the size of the sample, the observation dimension, and the number of runs, which give the number of rows and columns (and, if more than one run, slices) of the data array.

Slots

filename:

Object of class "character": the filename the data shall be saved

name:

Object of class "character": a name for the Data

Data:

Object of class "ArrayorNULLorVectororDataframeorSeqDataFrames": the actual data, either of type "NULL" (means no data) or "vector" or "array" or "Dataframe" or "SeqDataFrames"

obsDim:

Object of class "numeric": the observation dimension of the data

runs:

Object of class "numeric": the number of runs of the data

samplesize:

Object of class "numeric": the size of the sample

version:

Object of class "character": the package version under which this object was generated

Methods

Data

signature(object = "Dataclass"): returns the actual data

Data<-

signature(object = "Dataclass"): changes the data

evaluate

signature(object = "Dataclass", estimator = "function"):

creates an object of type "Evaluation", see there for further information

filename

signature(object = "Dataclass"): returns the the filename

filename<-

signature(object = "Dataclass"): changes the the filename

name

signature(object = "Dataclass"): returns the the name

name<-

signature(object = "Dataclass"): changes the the name

initialize

signature(.Object = "Dataclass"): initialize method

obsDim

signature(object = "Dataclass"): returns the dimension of the observations

runs

signature(object = "Dataclass"): returns the number of runs

samplesize

signature(object = "Dataclass"): returns the size of the sample

getVersion

signature(object = "Dataclass"): returns the version slot of this object

savedata

signature(object = "Dataclass"): saves the object in the directory of R and also a copy without data

plot

signature(x = "Dataclass"): produces a plot of the data matrix; ; for details confer plot-methods

print

signature(x = "Dataclass"): returns filename, the observation dimension, the number of runs and the size of the sample, and, if from a version > 1.8, also the package version under which the object was generated

summary

signature(object = "Dataclass"): returns the same information as print, moreover a statistical summary for each run

Note

The saved Dataclass can be loaded with the usual load-command, the saved comment with the function cload.

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

Simulation-class Contsimulation-class Evaluation-class plot-methods
print-methods summary-methods load cload savedata-methods getVersion-methods

Examples

D66 <- Dataclass(filename="N74", Data = matrix(1:36,6))
D66
#
D <- Dataclass(Data = array(c(1,2,3,4,5,6),c(samplesize=2,obsdim=3,Runs=1)),
               filename = "xyz.sav")
# A new object of type "Dataclass" is created.
#
isOldVersion(D) ##NO!
#
savedata(D)
# creates a file called "xyz.sav" where the information is saved and a
# copy "xyz.sav.comment" without data
Data(D) <- array(c(11,12,13,14,15,16),c(samplesize=2,obsdim=3,Runs=1)) # changes the data of D
cload("xyz.sav") # loads the object without data - it is called "D.comment"
D.comment
load("xyz.sav") # loads the original object "D"
Data(D) # the original data: matrix(c(1,2,3,4,5,6),2)
#if you have distrTEst available:
#evaluate(object = D, estimator = mean) # returns the mean of each variable
## clean up
unlink("xyz.sav")
unlink("xyz.sav.comment")

Class "SeqDataFrames"

Description

An object of type "SeqDataFrames" is a list of data frames, all of which with the same numbers and names of columns (ideally with the same data-types for the columns), but with possibly varying number of rows; with correponding index operators it behaves like a three-dimensional array with dimensions sample size x observation dimension x runs.

Details

There is a validity method checking for each member of the list being a data frame and for the accordance of the column structures of the data frames.

Objects from the Class

Objects can be created by calls of the form SeqDataFrames(...), where the ... are a list of dataframes with according column structure.

Slots

data:

a list of data frames

Methods

[

signature(x = "SeqDataFrames"): returns (slices of) the data

[<-

signature(x = "SeqDataFrames"): modifies (slices of) the data

print

signature(x = "SeqDataFrames", obs0 = NULL, dims0 = NULL, runs0 = NULL, short = FALSE, ...): slices can be printed and, if argument short== TRUE only a bounded number of dimensions is shown.

show

signature(object = "SeqDataFrames"): a call to print(x)

names

signature(x = "SeqDataFrames"): returns the names of the runs

runnames

signature(x = "SeqDataFrames"): returns the names of the runs

obsdimnames

signature(x = "SeqDataFrames"): returns the names of the observation dimensions

obsDim

signature(x = "SeqDataFrames"): returns the dimension of the observations

runs

signature(x = "SeqDataFrames"): returns the number of runs

samplesize

signature(x = "SeqDataFrames"): returns the size of the samples for each run

rbind

signature(x = "SeqDataFrames"): concatenates different a list of SeqDataFrames object (with the same column structure) to a new object of class SeqDataFrames to do so we mask the rbind method from package base

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

[-methods print-methods summary-methods

Class "Simulation"

Description

In an object of type Simulation data can be simulated in any distribution and size.

Objects from the Class

Objects can be created by calls of the form Simulation(filename, samplesize, runs, seed, distribution) (observation dimension is deduced from slot distribution). A Simulation-object includes a filename, a name for the simulation, the number of runs, the size of the sample, the seed and the distribution of the random numbers. The slot Data stays empty until the method simulate has been used.

Slots

seed:

Object of class "list": the seed the simulation has been generated with

distribution:

Object of class "UnivariateDistribution": the distribution of the random numbers

filename:

Object of class "character": the filename the simulation shall be saved

name:

Object of class "character": a name for the Simulation

Data:

Object of class "ArrayorNULLorVector": the simulated data

samplesize:

Object of class "numeric": the size of the sample

obsDim:

Object of class "numeric": the dimension of the observations of the data

runs:

Object of class "numeric": the number of runs of the data

version:

Object of class "character": the version of this package, under which this object was generated

Extends

Class "Dataclass", directly.

Methods

Data

signature(object = "Simulation"): returns the simulated data.

Data<-

signature(object = "Simulation"): ERROR: A modification of simulated data is not allowed.

filename

signature(object = "Simulation"): returns the the filename

filename<-

signature(object = "Simulation"): changes the the filename

name

signature(object = "Simulation"): returns the the name

name<-

signature(object = "Simulation"): changes the the name

distribution

signature(object = "Simulation"): returns the distribution

distribution<-

signature(object = "Simulation"): changes the distribution

seed

signature(object = "Simulation"): returns the seed

seed<-

signature(object = "Simulation"): changes the seed

obsDim

signature(object = "Simulation"): returns the dimension of the observations

getVersion

signature(object = "Simulation"): returns the version of this package, under which this object was generated

runs

signature(object = "Simulation"): returns the number of runs

runs<-

signature(object = "Simulation"): changes the number of runs

samplesize

signature(object = "Simulation"): returns the size of the sample

samplesize<-

signature(object = "Simulation"): changes the size of the sample

savedata

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

initialize

signature(.Object = "Simulation"): initialize method

plot

signature(x = "Simulation"): produces a plot of the data matrix; for details confer plot-methods

print

signature(x = "Simulation"): returns filename, seed, the observation dimension, the number of runs, the size of the sample, the distribution generating the simulations, and, if from a version > 1.8, also the package version under which the object was generated

show

signature(x = "Simulation"): the same as print.

simulate

signature(x = "Simulation"): generates the random numbers for the simulation

summary

signature(object = "Simulation"): returns filename, seed, number of runs, the size of the sample and a statistical summary for each run

Note

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

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

Dataclass-class Contsimulation-class plot-methods print-methods summary-methods simulate-methods getVersion-methods

Examples

N=Norm() # N is a standard normal distribution.
S=Simulation(filename="xyz",runs=10,samplesize=3,seed=setRNG(),distribution=N)
Data(S) # no data yet
simulate(S)
Data(S) # now there are random numbers
Data(S) # the same data as before because the seed has not changed
seed(S)=setRNG()
simulate(S)
Data(S) # different data
savedata(S) # saves the object in the directory of R...
load("xyz") # loads it again...
Data(S) # ...without the data - use simulate to return it!
unlink("xyz")

Subsetting/Indexing methods for SeqDataFrames objects in Package ‘distrSim’

Description

Operators acting on SeqDataFrames objects to extract or replace parts.

Usage

## S4 method for signature 'SeqDataFrames'
x[i, j, k, drop = FALSE]

## S4 replacement method for signature 'SeqDataFrames'
x[i, j, k] <- value

Arguments

Value

again an object of class SeqDataFrames with the prescribed indices / values

Methods

"["

signature(x = "SeqDataFrames"): access method for indices for objects of class SeqDataFrames

"[<-"

signature(x = "SeqDataFrames"): replacement method for indices for objects of class SeqDataFrames

See Also

"["

Examples

s0 <- matrix(1:6,3,2)
d0 <- data.frame(s0)
d1 <- data.frame(s0 + 3)
SF <- SeqDataFrames(d0, d1)
SF[1,2,1]

Methods for Version Management in Package ‘distrSim’

Description

Version-Management-methods

Usage

## S4 method for signature 'Dataclass'
getVersion(object)
## S4 method for signature 'Dataclass'
conv2NewVersion(object)

Arguments

Far-reaching Change in Design

From version 1.8 of this package on, we have changed the format how data / simulations are stored: In order to be able to cope with multivariate distributions, regression distributions and (later) time series distributions, we have switched to the common array format: samplesize x obsDim x runs; for saved objects from earlier versions, we provide the functions isOldVersion (from package distr) and conv2NewVersion to check whether the object was generated by an older version of this package and to convert such an object to the new format, respectively.

Methods

getVersion

signature(object = "Dataclass"): returns slot version of an object of class "Dataclass".

conv2NewVersion

signature(object = "Dataclass"): changes an object with format runs x samplesize (old format) to samplesize x obsDim x runs (new format)

See Also

isOldVersion, conv2NewVersion

cload

Description

loads the comment file from a saved Dataclass object

Usage

cload(filename)

Arguments

Details

Uses function load to load the comment file from a saved Dataclass object.

Value

no value is returned

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

Dataclass-class load savedata-methods

Examples

# see Dataclass and Evaluation for examples
## The function is currently defined as
function(filename){
  eval.parent(parse(text=paste("load(\"",filename,".comment\")", sep = "")))
  }

Masking of/by other functions in package "distrSim"

Description

Provides information on the (intended) masking of and (non-intended) masking by other other functions in package distrSim

Usage

distrSimMASK(library = NULL)

Arguments

Value

no value is returned

Author(s)

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de

Examples

## IGNORE_RDIFF_BEGIN
distrSimMASK()
## IGNORE_RDIFF_END

functions to change the global variables of the package ‘distrSim’

Description

With distrSimoptions and getdistrSimOption you may inspect and change the global variables used by package distrSim.

Usage

distrSimoptions(...)
getdistrSimOption(x)

Arguments

Details

Invoking distrSimoptions() with no arguments returns a list with the current values of the options. To access the value of a single option, one should use getdistrSimOption("MaxNumberofSummarizedRuns"), e.g., rather than distroptions("MaxNumberofSummarizedRuns") which is a list of length one.

Value

distrSimoptions() returns a list of the global options of distrSim.
distrSimoptions("MaxNumberofSummarizedRuns") returns the global option MaxNumberofSummarizedRuns as a list of length 1.
distrSimoptions("MaxNumberofSummarizedRuns" = 3) sets the value of the global option MaxNumberofSummarizedRuns to 3. getdistrSimOption("MaxNumberofSummarizedRuns") the current value set for option MaxNumberofSummarizedRuns.

Currently available options

MaxNumberofPlottedObs

maximal number of observation plotted; defaults to 4000

MaxNumberofPlottedObsDims

maximal number of observation dimensions plotted in parallel; defaults to 6

MaxNumberofPlottedRuns

maximal number of runs plotted in parallel; defaults to 6

MaxNumberofSummarizedObsDims

maximal number of observation dimensions summarized in parallel; defaults to 6

MaxNumberofSummarizedRuns

maximal number of runs summarized in parallel; defaults to 6

Author(s)

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de

See Also

options, getOption, distroptions, getdistrOption

Examples

distrSimoptions()
distrSimoptions("MaxNumberofPlottedObsDims")
distrSimoptions("MaxNumberofPlottedObsDims" = 5)
# or
getdistrSimOption("MaxNumberofPlottedObsDims")

Methods for Function distribution in Package ‘distrSim’

Description

distribution-methods

Methods

distribution

signature(object = "Simulation"): returns the slot distribution of the simulation

distribution<-

signature(object = "Simulation"): changes the slot distribution of the simulation

Methods for Function distribution.c in Package ‘distrSim’

Description

distribution-methods

Methods

distribution.c

signature(object = "Contsimulation"): returns the distribution of the contaminated data

distribution.c<-

signature(object = "Contsimulation"): changes the distribution of the contaminated data

Methods for Function distribution.id in Package ‘distrSim’

Description

distribution-methods

Methods

distribution.id

signature(object = "Contsimulation"): returns the distribution of the ideal data

distribution.id<-

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

Methods for Function filename in Package ‘distrSim’

Description

filename-methods

Methods

filename

signature(object = "Dataclass"): returns the filename

filename<-

signature(object = "Dataclass"): changes the filename

Methods for Function ind in Package ‘distrSim’

Description

ind-methods

Methods

ind

signature(object = "Contsimulation"): returns an indicator showing which data is contaminated

Methods for Function name in Package ‘distrSim’

Description

name-methods

Methods

name

signature(object = "Dataclass"): returns the name

name<-

signature(object = "Dataclass"): changes the name

Methods for Function obsDim in Package ‘distrSim’

Description

obsDim-methods

Methods

obsDim

signature(object = "Dataclass") or signature(object = "SeqDataFrames"): returns the number of obsDim

Methods for Function plot in Package ‘distrSim’

Description

plot-methods

Value

An S3 object of class c("plotInfo","DiagnInfo"), i.e., a list containing the information needed to produce the respective plot, which at a later stage could be used by different graphic engines (like, e.g. ggplot) to produce the plot in a different framework. A more detailed description will follow in a subsequent version.

Methods

plot

signature(x = "Dataclass", y="missing"): produces a plot of the data matrix; optional arguments:

obs0

the indices of observations to be plotted;— of this vector runs0 maximally MaxNumberofPlottedObs runs are plotted where MaxNumberofPlottedObs is a global option, see distrSimoptions

runs0

the indices of runs to be plotted; — of this vector runs0 maximally MaxNumberofPlottedRuns runs are plotted where MaxNumberofPlottedRuns is a global option, see distrSimoptions

dims0

the indices of observation dimensions to be plotted; — of this vector dims0 maximally MaxNumberofPlottedObsDims dimensions are plotted where MaxNumberofPlottedObsDims is a global option, see distrSimoptions

typical plot arguments may be passed; some have slightly different meaning (compare plot.default):

ylim

may be transmitted matrixwise (in a 2 x (number of dimensions) matrix)) or globally, using the usual recycling rules

col,cex,pch

may be transmitted vectorwise (for the different dimensions) or globally, using the usual recycling rules

xlab,ylab,type

are ignored

plot

signature(x = "Simulation", y="missing"): produces a plot of the data matrix; optional and typical plot arguments: as with signature(x = "Dataclass", y="missing")

plot

signature(x = "Contsimulation"): produces a plot of the real data matrix; optional arguments: as with signature(x = "Dataclass", y="missing"); typical plot arguments may be passed; some have slightly different meaning (compare plot.default):

ylim

as with signature(x = "Simulation", y="missing") and signature(x = "Dataclass", y="missing")

col,cex,pch

are ignored

col.id,cex.id,pch.id

as col,cex,pch for signature(x = "Dataclass", y="missing") but only for ideal part of the data

col.c,cex.c,pch.c

as col,cex,pch for signature(x = "Dataclass", y="missing") but only for contaminated part of the data

xlab,ylab,type

are ignored

Methods for Function print/show in Package ‘distrSim’

Description

print and show - methods

Methods

print

signature(x = "SeqDataFrames"): extra argument short = FALSE; if TRUE the output is cut according to distrSimoptions.

print

signature(x = "Dataclass"): returns name, filename, the observation dimension, the number of runs and the size of the sample, and, if from a version > 1.8, also the package version under which the object was generated

print

signature(x = "Simulation"): as for signature(x = "Dataclass") and, additionally, seed and the distribution

print

signature(x = "Contsimulation"): as for signature(x = "Dataclass") and, additionally, seed, the contamination rate and the distributions

show

signature(x = "Dataclass"), signature(x = "Simulation"), signature(x = "Contsimulation"), signature(x = "SeqDataFrames"): as corresponding print method

Methods for Function rate in Package ‘distrSim’

Description

rate-methods

Methods

rate

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

rate<-

signature(object = "Contsimulation"): modifies the contamination rate

Methods for Function runs in Package ‘distrSim’

Description

runs-methods

Methods

runs

signature(object = "SeqDataFrames"): returns the number of runs

runs

signature(object = "Dataclass"): returns the number of runs

runs<-

signature(object = "Simulation"): changes the number of runs

runs<-

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

Methods for Function samplesize in Package ‘distrSim’

Description

samplesize-methods

Methods

samplesize

signature(object = "SeqDataFrames"): returns the size[s] of the sample[s]

samplesize

signature(object = "Dataclass"): returns the size of the sample

samplesize<-

signature(object = "Simulation"): changes the size of the sample

samplesize<-

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

Methods for Function savedata in Package ‘distrSim’

Description

savedata-methods

Methods

savedata

signature(object = "Dataclass"): saves the object (with the data) in the directory of R

savedata

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

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.)

Note

For an example, see Simulation-class and Contsimulation-class

See Also

Dataclass-class Simulation-class Contsimulation-class Evaluation-class

Methods for Function seed in Package ‘distrSim’

Description

seed-methods

Methods

seed

signature(object = "Simulation"): returns the slot seed of an object of class "Simulation"

seed<-

signature(object = "Simulation"): changes the slot seed of an object of class "Simulation"

seed

signature(object = "Contsimulation"): returns the slot seed of an object of class "Contsimulation"

seed<-

signature(object = "Contsimulation"): changes the slot seed of an object of class "Contsimulation"

Note

The value to which the seed is set has to be consistent with the setRNG-package; to draw a “new” simulation, use something like seed(X)<-setRNG();simulate(X); cf. manual to this package, p.~9

Methods for Function simulate in Package ‘distrSim’

Description

simulate-methods

Methods

simulate

signature(object = "Simulation"): generates the random numbers for the simulation

simulate

signature(object = "Contsimulation"): generates the random numbers for the simulation

Methods for Function summary in Package 'distrSim'

Description

summary-methods

Methods

summary

signature(object = "Dataclass"): returns the same information as print, moreover a statistical summary for each run; optional arguments:

runs0

the indices of runs to be summarized; — of this vector runs0 maximally MaxNumberofSummarizedRuns runs are summarized where MaxNumberofSummarizedRuns is a global option, see distrSimoptions

dims0

the indices of observation dimensions to be summarized; — of this vector dims0 maximally MaxNumberofSummarizedObsDims dimensions are summarized where MaxNumberofSummarizedObsDims is a global option, see distrSimoptions

summary

signature(object = "Simulation"): returns name, filename, seed, number of runs, the size of the sample and a statistical summary for each run; optional arguments: as with signature(object = "Dataclass")

summary

signature(object = "Contsimulation"): returns name, filename, seed, number of runs, the size of the sample, the rate and a statistical summary for each run of the real data; optional arguments: as with signature(object = "Dataclass")

Classes "vectororNULL", "MatrixorNULLorVector", "ArrayorNULLorVector", "DataframeorSeqDataFrame" and "ArrayorNULLorVectororDataframeorSeqDataFrames"

Description

auxiliary classes; may contain either a vector or NULL, [or a matrix, or an array, respectively], cf. J. Chambers, "green book".

Objects from the Classes

these classes are all virtual: No objects may be created from it.

Methods

No methods defined with classs "vectororNULL", "MatrixorNULLorVector", and "ArrayorNULLorVectororDataframeorSeqDataFrames" in the signature. However, the generating function Dataclass dispatches according to "DataframeorSeqDataFrames" or "ArrayorNULLorVector".

Note

Dataclass-class can save data either of type "NULL" (means no data) or "vector" or "array" or "data.frame"

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

See Also

Dataclass-class