Description Usage Arguments Details Value Author(s) References Examples
This function create the bias-corrected accelerated bootstrap confidence intervals based on the trimmed elemental regressions.
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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 a 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 numeric 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. |
est.TEE |
this is for trimmed elemental regression estimates. |
conf.level |
the confidence level. |
n.boot |
number of bootstrap samples. |
For discussions about bootstrap confidence intervals and coverage probabilities of regression parameter estimates using trimmed elemental estimation, see Hall and Mayo (2008).
call |
call to the function. |
ci |
bias-corrected accelerated bootstrap confidence interval estimates for the regression parameters. |
Wei Jiang and Matthew S. Mayo
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.
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