sampSurf (version 0.7-6)

controlVariate: Generate Objects of Class "'>controlVariate"

Description

This generic has two methods, they are used to apply control variate subsampling to an individual "Stem" object, or collections of "Stem" objects. See controlVariate-methods for details.

Usage

controlVariate(object, ...)

Arguments

object

This is the signature argument, see the controlVariate-methods for possible values.

…

Arguments that can be passed along to the proxy function.

Value

A valid object of class "'>controlVariate" or "'>mcsContainer", depending on which method was used.

Details

Control variate sampling uses the differences between measured and proxy model cross-sectional areas to estimate the volume of a bole section. Control variate sampling is sensitive to departures of the proxy from the true bole, and can actually produce negative volumes. See the examples in the vignette reference below for examples illustrating this phenomenon.

References

%

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

See Also

See controlVariate-methods for methods. Other similar generics for Monte Carlo methods include: crudeMonteCarlo, importanceSampling, antitheticSampling.

Examples

# NOT RUN {
#
# estimate volume between 10 and 15 m, using 5 random heights...
#
sTree = standingTree(dbh = 40, topDiam = 0, height = 20, solidType = 2.8)
sTree.cv = controlVariate(sTree, n.s = 5, segBnds = c(10,15), startSeed = 114,
           proxy = 'wbProxy', solidTypeProxy = 2.5, truncateProxyStem = FALSE)
sTree.cv
# }