mcsContainer: Generate Objects of Class "'mcsContainer'"

In sampSurf: Sampling Surface Simulation for Areal Sampling Methods

Description

The methods for this function will allow the creation of valid "mcsContainer" class objects. Please note that it is preferable to use the constructors named after the Monte Carlo method being used, rather than calling this function directly. For example, to use importance sampling, call the importanceSampling constructor with a container of "Stem" subclass objects. Please see the vignette below for detailed examples. See also mcsContainer-methods for method details.

Usage

mcsContainer(object, ...)

Arguments

object	The signature object for the generic.
...	Just gobbled presently.

Details

The vignette below gives examples on creating "mcsContainer" objects for each of the Monte Carlo subsampling methods available in sampSurf. The respective methods are simpler to use and more intuitive, and their use will ensure that a valid container object is returned.

Value

A valid object of class "mcsContainer."

Note

Please note that this is not a completely functional container class in the traditional sense at present as it does not have replacement, deletion, or addition functions. If you need to do any of these operations, perform them on the list object (in the mcsObjs slot) and then recreate the container. If the object is not re-built after, e.g., deletion, the summary statistics will be incorrect.

Author(s)

Jeffrey H. Gove

References

Gove, J. H. 2013. Monte Carlo sampling methods in sampSurf. Package vignette.

See Also

Please see the direct constructors: crudeMonteCarlo, importanceSampling and controlVariate for methods to create collections of objects under these subsampling schemes. For antithetic versions of these methods, see the antitheticContainer class.

Examples

sTrees = standingTrees(5, startSeed = 12)
sTrees.cmc = crudeMonteCarlo(sTrees, n.s = 10)
sTrees.cmc
print(sTrees.cmc@stats, digits = 4)

sampSurf documentation built on March 5, 2021, 3:01 p.m.