Class for controlling model-based generation of data.
Objects can be created by calls of the form new("DataControl", …)
or
DataControl(…)
.
size
:Object of class "numeric"
giving the number of
observations to be generated.
distribution
:Object of class "function"
generating
the data, e.g., rnorm
(the default) or
rmvnorm
from package mvtnorm. It should take a positive
integer as its first argument, giving the number of observations to be
generated, and return an object that can be coerced to a
data.frame
.
dots
:Object of class "list"
containing additional
arguments to be passed to distribution
.
colnames
:Object of class "OptCharacter"
; a character
vector to be used as column names for the generated data.frame
, or
NULL
.
Class "'>VirtualDataControl"
, directly.
Class "'>OptDataControl"
, by class "VirtualDataControl", distance 2.
getSize
signature(x = "DataControl")
: get slot
size
.
setSize
signature(x = "DataControl")
: set slot
size
.
getDistribution
signature(x = "DataControl")
: get slot
distribution
.
setDistribution
signature(x = "DataControl")
: set slot
distribution
.
getDots
signature(x = "DataControl")
: get slot
dots
.
setDots
signature(x = "DataControl")
: set slot
dots
.
getColnames
signature(x = "DataControl")
: get slot
colnames
.
setColnames
signature(x = "DataControl")
: set slot
colnames
.
In addition to the methods inherited from
"'>VirtualDataControl"
, the following are available:
generate
signature(control = "DataControl")
: generate
data.
show
signature(object = "DataControl")
: print the
object on the R console.
A slightly simplified UML class diagram of the framework can be found in
Figure 1 of the package vignette An Object-Oriented Framework for
Statistical Simulation: The R Package simFrame
. Use
vignette("simFrame-intro")
to view this vignette.
Alfons, A., Templ, M. and Filzmoser, P. (2010) An Object-Oriented Framework for Statistical Simulation: The R Package simFrame. Journal of Statistical Software, 37(3), 1--36. 10.18637/jss.v037.i03.
"'>VirtualDataControl"
, generate
# NOT RUN {
dc <- DataControl(size = 10, distribution = rnorm,
dots = list(mean = 0, sd = 2))
generate(dc)
# }
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