SimControl-class {simFrame}R Documentation

Class "SimControl"

Description

Class for controlling how simulation runs are performed.

Objects from the Class

Objects can be created by calls of the form new("SimControl", ...) or SimControl(...).

Slots

contControl:
Object of class "OptContControl"; a control object for contamination, or NULL.
NAControl:
Object of class "OptNAControl"; a control object for inserting missing values, or NULL.
design:
Object of class "character" specifying the variables (columns) to be used for splitting the data into domains. The simulations, including contamination and the insertion of missing values (unless SAE=TRUE), are then performed on every domain.
fun:
Object of class "function" to be applied in each simulation run.
dots:
Object of class "list" containing additional arguments to be passed to fun.
SAE:
Object of class "logical" indicating whether small area estimation will be used in the simulation.

Details

There are some requirements for fun. It must return a numeric vector or an object of class "SimResult", which consists of a slot values (a numeric vector) and a slot add (additional results of any class, e.g., statistical models). Note that the latter is computationally more expensive. Returning a list with components values and add is also accepted and slightly faster than using a "SimResult" object. A data.frame is passed to fun in every simulation run. The corresponding argument must be called x. If comparisons with the original data need to be made, e.g., for evaluating the quality of imputation methods, the function should have an argument called orig. If different domains are used in the simulation, the indices of the current domain can be passed to the function via an argument called domain.

For small area estimation, the following points have to be kept in mind. The design for splitting the data must be supplied and SAE must be set to TRUE. However, the data are not actually split into the specified domains. Instead, the whole data set (sample) is passed to fun. Also contamination and missing values are added to the whole data (sample). Last, but not least, the function must have a domain argument so that the current domain can be extracted from the whole data (sample).

In every simulation run, fun is evaluated using try. Hence no results are lost if computations fail in any of the simulation runs.

Methods

clusterRunSimulation
signature(cl = "ANY", x = "data.frame", setup = "VirtualSampleControl", nrep = "missing", control = "SimControl"): run a simulation experiment on a snow cluster.
clusterRunSimulation
signature(cl = "ANY", x = "data.frame", setup = "SampleSetup", nrep = "missing", control = "SimControl"): run a simulation experiment on a snow cluster.
clusterRunSimulation
signature(cl = "ANY", x = "VirtualDataControl", setup = "missing", nrep = "numeric", control = "SimControl"): run a simulation experiment on a snow cluster.
runSimulation
signature(x = "data.frame", setup = "VirtualSampleControl", nrep = "missing", control = "SimControl"): run a simulation experiment.
runSimulation
signature(x = "data.frame", setup = "SampleSetup", nrep = "missing", control = "SimControl"): run a simulation experiment.
runSimulation
signature(x = "data.frame", setup = "missing", nrep = "numeric", control = "SimControl"): run a simulation experiment.
runSimulation
signature(x = "data.frame", setup = "missing", nrep = "missing", control = "SimControl"): run a simulation experiment.
runSimulation
signature(x = "VirtualDataControl", setup = "missing", nrep = "numeric", control = "SimControl"): run a simulation experiment.
runSimulation
signature(x = "VirtualDataControl", setup = "missing", nrep = "missing", control = "SimControl"): run a simulation experiment.

Author(s)

Andreas Alfons, alfons@statistik.tuwien.ac.at

See Also

runSimulation, SimResults

Examples

showClass("SimControl")

[Package simFrame version 0.1.1 Index]