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A key result in Efron's seminal paper that introduced the bootstrap [4] is the favorable performance of bootstrap methods using sampling with replacement compared to prior methods like the jackknife that sample without replacement. However, since its introduction, numerous variants on the bootstrap have been proposed, including methods that ...
The best example of the plug-in principle, the bootstrapping method. Bootstrapping is a statistical method for estimating the sampling distribution of an estimator by sampling with replacement from the original sample, most often with the purpose of deriving robust estimates of standard errors and confidence intervals of a population parameter like a mean, median, proportion, odds ratio ...
In general, bootstrapping usually refers to a self-starting process that is supposed to continue or grow without external input. Many analytical techniques are often called bootstrap methods in reference to their self-starting or self-supporting implementation, such as bootstrapping (statistics), bootstrapping (finance), or bootstrapping (linguistics).
One set, the bootstrap sample, is the data chosen to be "in-the-bag" by sampling with replacement. The out-of-bag set is all data not chosen in the sampling process. When this process is repeated, such as when building a random forest, many bootstrap samples and OOB sets are created. The OOB sets can be aggregated into one dataset, but each ...
The Power of 10 Rules were created in 2006 by Gerard J. Holzmann of the NASA/JPL Laboratory for Reliable Software. [1] The rules are intended to eliminate certain C coding practices that make code difficult to review or statically analyze.
Within an integrated circuit a bootstrap method is used to allow internal address and clock distribution lines to have an increased voltage swing. The bootstrap circuit uses a coupling capacitor, formed from the gate/source capacitance of a transistor, to drive a signal line to slightly greater than the supply voltage. [10]
The modern usage of the term "conformal bootstrap" was introduced in 1984 by Belavin et al. [7] In the earlier literature, the name was sometimes used to denote a different approach to conformal field theories, nowadays referred to as the skeleton expansion or the "old bootstrap". This older method is perturbative in nature, [13] [14] and is ...
From 1950 to 1996, all the publications on particle filters, and genetic algorithms, including the pruning and resample Monte Carlo methods introduced in computational physics and molecular chemistry, present natural and heuristic-like algorithms applied to different situations without a single proof of their consistency, nor a discussion on the bias of the estimates and genealogical and ...