Bootstrapping

Known as: Bootstrap, Bootstrap method, Bootstrap sampling 
In statistics, bootstrapping can refer to any test or metric that relies on random sampling with replacement. Bootstrapping allows assigning measures… (More)
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Topic mentions per year

Topic mentions per year

1985-2017
010203019852017

Papers overview

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Highly Cited
2011
Highly Cited
2011
Most knowledge sources on the Data Web were extracted from structured or semi-structured data. Thus, they encompass solely a… (More)
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Highly Cited
2009
Highly Cited
2009
The bootstrap problem is often recognized as one of the main challenges of evolutionary robotics: if all individuals from the… (More)
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2008
2008
Simulation methods, in particular Efron's (1979) bootstrap, are being applied more and more widely in statistical inference… (More)
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2007
2007
M-estim::ztes The bootstrap principle is justified for robust M-estimates in regression. (A short proof justifying bootstrapping… (More)
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2005
2005
Bootstrapping techniques are an efficient way to develop electronic pronunciation dictionaries [1, 2], but require fast system… (More)
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2005
2005
In this paper, we propose bootstrap methods for statistics evaluated on high frequency data such as realized volatility. The… (More)
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Highly Cited
2004
Highly Cited
2004
The Kalman filter provides an effective solution to the linear-Gaussian filtering problem. However, where there is nonlinearity… (More)
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2002
2002
In this paper, we consider bootstrapping cointegrating regressions. It is shown that the method of bootstrap, if properly… (More)
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Highly Cited
1999
Highly Cited
1999
This paper develops a consistent bootstrap estimation procedure for obtaining con®dence intervals for Malmquist indices of… (More)
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Highly Cited
1991
Highly Cited
1991
The bootstrap method provides a powerful, general procedure for estimating the variance of a parameter of a function. The… (More)
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