Bootstrapping Regression Models

@inproceedings{Fox2002BootstrappingRM,
  title={Bootstrapping Regression Models},
  author={John Fox},
  year={2002}
}
Bootstrapping is a general approach to statistical inference based on building a sampling distribution for a statistic by resampling from the data at hand. The term ‘bootstrapping,’ due to Efron (1979), is an allusion to the expression ‘pulling oneself up by one’s bootstraps’ – in this case, using the sample data as a population from which repeated samples are drawn. At first blush, the approach seems circular, but has been shown to be sound. Two S libraries for bootstrapping are associated… CONTINUE READING
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Bootstrap Methods and their Application

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3 Excerpts

Bootstrap Methods: Another Look at the Jackknife.

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