importanceSampling: Generate Objects of Class "'importanceSampling'"
In sampSurf: Sampling Surface Simulation for Areal Sampling Methods

Description Usage Arguments Details Value Author(s) References See Also Examples

This generic has five methods, they are used to apply importance (sub) sampling to an individual "Stem" object, or collections of "Stem" objects. See importanceSampling-methods for details.

1	importanceSampling(object, ...)

`object`	This is the signature argument, see the `importanceSampling-methods` for possible values.
`...`	Arguments that can be passed along to the proxy function.

Briefly, with importance sampling for bole volume (or some segment of the bole) one uses a proxy taper function from which to draw samples and thereby concentrate the samples in the lower portion of the bole, where there is more volume and measurements are easier. The diferent built-in proxy functions and their use are detailed in the vignette cited below. In addition, one can supply one's own proxy function if desired.

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

Jeffrey H. Gove

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

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

#
# estimate volume between 10 and 15 m, using 5 random heights...
#
sTree = standingTree(dbh = 40, topDiam = 0, height = 20, solidType = 2.8)
sTree.is = importanceSampling(sTree, n.s = 5, segBnds = c(10,15), startSeed = 114,
           proxy = 'wbProxy', solidTypeProxy = 2.5)
sTree.is