TEEReg-package: Trimmed Elemental Estimation for Linear Models.

Description Details Author(s) References Examples

Description

Package provides functions for computing the trimmed elemental estimates, as well as for creating the bias-corrected and accelerated bootstrap confidence intervals based on trimmed elemental regressions. This approach offers a robust alternative to ordinary least squares.

Details

Package: TEEReg
Type: Package
Version: 1.1
Date: 2016-06-12
License: GPL (version 2 or later)

There are two major functions in the package. The TEE function is for computing the trimmed elemental estimates. The TEE.BCa function is for creating the bias-corrected accelerated bootstrap confidence intervals for regression parameters.

Author(s)

Wei Jiang and Matthew S. Mayo

Maintainer: Wei Jiang <[email protected]>

References

M. S. Mayo and B. Gray. Elemental subsets: the building blocks of regression. The American Statistician, 51: 122-129, 1997.

M. Hall and M. S. Mayo. Bootstrap confidence intervals and coverage probabilities of regression parameter estimates using trimmed elemental estimation. Journal of Modern Applied Statistical Methods, 7: 514-525, 2008.

Examples

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data(telephone)
fit <- TEE(formula=Y~X,data=telephone,p.trimmed=0.5,p.subsample=0.5,method="tee")
TEE.BCa(formula=Y~X,data=telephone,est.TEE=fit$coefficients,p.trimmed=0.5,p.subsample=0.5,
method="tee",conf.level=0.05,n.boot=20)

Example output

$call
TEE.BCa(formula = Y ~ X, data = telephone, p.trimmed = 0.5, p.subsample = 0.5, 
    method = "tee", est.TEE = fit$coefficients, conf.level = 0.05, 
    n.boot = 20)

$ci
            estimates(TEE) Lower limit Upper limit
(Intercept)     -59.838079  -71.485059  -50.786948
X                 1.236983    1.077209    1.435576

TEEReg documentation built on May 30, 2017, 7:20 a.m.