TEE: Compute the trimmed elemental estimates.

In TEEReg: Trimmed Elemental Estimation for Linear Models

Description

This function computes the trimmed elemental estimates for regression parameters.

Usage

TEE(formula,data,offset=NULL,p.trimmed=NULL,p.subsample=1,method="tee")

Arguments

formula	define a symbolic description of the model to be fitted.
data	specify the dataset used for performing regression analysis. It must be formatted in data frame.
offset	specify an known component to be included in the linear predictor during fitting. This argument should be either NULL or a numeric vector with length equal to the number of observations.
p.trimmed	define the trimming proportion of elemental subsets. This should be either NULL or a numeric value between 0 and 1. When method = "tee" is specified, a numberic value must be provided.
p.subsample	this is the proportion of subsampling with values between 0 and 1. The default value is 1, meaning that calculations are based on the full data.
method	two options are supported: "ols" stands for ordinary least squares and "tee" stands for trimmed elemental estimation.

Details

For more details about trimmed elemental estimation, see Mayo and Gray (1997).

Value

call	call to the function.
coefficients	estimated regression coefficients with intercept.
residuals	residuals resulted from the fitted model, i.e. y - yhat.
fitted.values	values fitted by the model, i.e. yhat = x betahat.

Author(s)

Wei Jiang and Matthew S. Mayo

References

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

Examples

data(telephone)
fit<-TEE(formula=Y~X,data=telephone,p.trimmed=0.5,p.subsample=0.5,method="tee")

TEEReg documentation built on May 2, 2019, 3:38 p.m.