boot.ci.M: Bootstrap CI of M-estimators differences of two samples

In asbio: A Collection of Statistical Tools for Biologists

Bootstrap CI of M-estimators differences of two samples

Description

Creates a bootstrap confidence interval for location differences for two samples. The default location estimator is the Huber one-step estimator, although any estimator can be used. The function is based on a function written by Wilcox (2005). Note, importantly, that P-values may be in conflict with the confidence interval bounds.

Usage

boot.ci.M(X1, X2, alpha = 0.05, est = huber.one.step, R = 1000)

Arguments

X1	Sample from population one.
X2	Sample from population two.
alpha	Significance level.
est	Location estimator; default is the Huber one step estimator.
R	Number of bootstrap samples.

Value

Returns a list with one component, a dataframe containing summary information from the analysis:

R.used	The number of bootstrap samples used. This may not = R if NAs occur because MAD = 0.
ci.type	The method used to construct the confidence interval.
conf	The level of confidence used.
se	The bootstrap distribution of differences standard error.
original	The original, observed difference.
lower	Lower confidence bound.
upper	Upper confidence bound.

Author(s)

Ken Aho and R. R. Wilcox from whom I stole liberally from code in the function m2ci on R-forge

References

Manly, B. F. J. (1997) Randomization and Monte Carlo methods in Biology, 2nd edition. Chapman and Hall, London.

Wilcox, R. R. (2005) Introduction to Robust Estimation and Hypothesis Testing, 2nd edition. Elsevier, Burlington, MA.

See Also

bootstrap, ci.boot

Examples

## Not run: 
X1<-rnorm(100,2,2.5)
X2<-rnorm(100,3,3)
boot.ci.M(X1,X2)

## End(Not run)

asbio documentation built on Aug. 20, 2023, 9:07 a.m.