Bootstrapping A technique for simulating new data sets, to assess the robustness of a model or to produce a set of likely models.
Bootstrapping a sample then goes along the following lines :
Many bootstrap samples are created from the unique original sample.
The statistic Z(X1, X2, ..., Xn) is calculated for each bootstrap sample.
Bootstrapping - this technique (Efron, 1979) samples a data set with replacement (i.e. a single case may be randomly sampled several times into the bootstrap set). The bootstrap can be applied any number of times, for increased accuracy.
Minimal Requirements for the Darwinian Bootstrapping of Quality," Journal of Memetics 1:1.
George B. Dyson (1998), Darwin Among the Machines: The Evolution of Global Intelligence (Perseus 1997)(1998) ISBN 0-7382-0030-1.
J. M.
Development of computer technology makes bootstrapping data becomes much easier than ever.
scientists, Ray Kurzweil and Hans Moravec, came out independently with serious books that proclaimed that in the coming century, our own computational technology, marching to the exponential drum of Moore's Law and more general laws of bootstrapping, ...
Simulator tools (namely bootstrapping) provide values for the uncertainty of alternative estimators.
Assumptions not satisfied ...
20.5 Minimally Supervised WSD: Bootstrapping
20.6 Word Similarity: Thesaurus Methods
20.7 Word Similarity: Distributional Methods ...
This notion of "bootstrapping"-that is, applying a problem-solving system to the task of improving some of its own methods-is old and famil1ar, but in [15] we find perhaps the first specific proposal about how such an advance might be realized.
 See also: Bootstrap, Regression, Distribution, Variance, Confidence interval
  
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