randboot: Bootstrap simulations

In ade4: Analysis of Ecological Data: Exploratory and Euclidean Methods in Environmental Sciences

Bootstrap simulations

Description

Functions and classes to manage outputs of bootstrap simulations for one (class randboot) or several (class krandboot) statistics

Usage

as.krandboot(obs, boot, quantiles = c(0.025, 0.975), names =
colnames(boot), call = match.call())
## S3 method for class 'krandboot'
print(x, ...)
as.randboot(obs, boot, quantiles = c(0.025, 0.975), call = match.call())
## S3 method for class 'randboot'
print(x, ...)
randboot(object, ...)

Arguments

obs	a value (class randboot) or a vector (class krandboot) with observed statistics
boot	a vector (class randboot) or a matrix (class krandboot) with the bootstrap values of the statistics
quantiles	a vector indicating the lower and upper quantiles to compute
names	a vector of names for the statistics
call	the matching call
x	an object of class randboot or krandboot
object	an object on which bootstrap should be perform
...	other arguments to be passed to methods

Value

an object of class randboot or krandboot

Author(s)

Stéphane Dray ([e-mail])

References

Carpenter, J. and Bithell, J. (2000) Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians.Statistics in medicine, 19, 1141-1164

See Also

randboot.multiblock

Examples

## an example corresponding to 10 statistics and 100 repetitions
bt <- as.krandboot(obs = rnorm(10), boot = matrix(rnorm(1000), nrow = 100))
bt
if(adegraphicsLoaded())
plot(bt) 

ade4 documentation built on Feb. 16, 2023, 7:58 p.m.