monteBSSample-class: Class '"monteBSSample"'

In sampSurf: Sampling Surface Simulation for Areal Sampling Methods

Description

This class contains the necessary structure for doing Monte Carlo sample size experiments under bootstrap sampling.

Objects from the Class

Objects can be created by calls of the form new("monteBSSample", ...). However, it is preferable to use the constructor method of the same name monteBSSample to minimize problems with potentially invalid objects.

Slots

degenerate:

Object of class "numeric": It may happen that, especially for small n, some of the samples drawn from the population can be degenerate (all the same value). When this happens, all of the bootstrap resamples will also be degenerate, and confidence interval estimation is impossible since it is based on the distribution of the bootstrap sample means. This slot is a numeric vector with the number of degenerate samples for each sample size in the n slot of the object.

R:

Object of class "numeric": The number of bootstrap sample replications.

means:

Object of class "data.frame": The data frame contains the overall bootstrap sample means for each of the mcSamples by length(n) samples drawn from the population. The overall bootstrap sample mean is defined here as the mean of the R individual (second-stage) bootstrap sample means for each case. Taking column means gives the overall mean for each of the sample sizes.

lowerCIs:

Object of class "data.frame": This is the lower “BCa” confidence interval endpoint for the 1-α/2 confidence level. It is calculated from the distribution of bootstrap sample means that is created in bootstrap sampling for each Monte Carlo sample and sample size, n.

upperCIs:

Object of class "data.frame": This is the upper “BCa” confidence interval endpoint for the 1-α/2 confidence level. It is calculated from the distribution of bootstrap sample means that is created in bootstrap sampling for each Monte Carlo sample and sample size, n.

Extends

Class "monteSample", directly.
Class "monteBSSampleOrNULL", directly.

Methods

summary

signature(object = "monteBSSample"): Object summary.

Author(s)

Jeffrey H. Gove

References

The ‘“monte”: When is n Sufficiently Large?’ vignette.

See Also

monte, montePop

Examples

showClass("monteBSSample")

sampSurf documentation built on March 5, 2021, 5:06 p.m.