Results 221 to 230 of about 300,617 (266)
Bootstrap tests: how many bootstraps? [PDF]
Econometric Reviews, 2000 In practice, bootstrap tests must use a finite number of bootstrap samples. This means that the outcome of the test will depend on the sequence of random numbers used to generate the bootstrap samples, and it necessarily results in some loss of power.
Russell Davidson, James G Mackinnon
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Bootstrapping heteroskedastic regression models: wild bootstrap vs. pairs bootstrap [PDF]
Computational Statistics and Data Analysis, 2005 In regression models, appropriate bootstrap methods for inference robust to heteroskedasticity of unknown form are the wild bootstrap and the pairs bootstrap. The finite sample performance of a heteroskedastic-robust test is investigated with Monte Carlo experiments.
Emmanuel Flachaire
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Journal of Cryptology, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Shai Halevi, Victor Shoup
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Shai Halevi, Victor Shoup
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IEEE Transactions on Automatic Control, 2006
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Mattias Aronsson +4 more
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Mattias Aronsson +4 more
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Infection Control & Hospital Epidemiology, 1994
Two questions confront data analysts: What's going on in the data? And how certain are the conclusions? One must deal with both questions to make rational decisions. John Tukey has called the two aspects of analysis exploratory and confirmatory. Consider, for example, a study in which patient
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Two questions confront data analysts: What's going on in the data? And how certain are the conclusions? One must deal with both questions to make rational decisions. John Tukey has called the two aspects of analysis exploratory and confirmatory. Consider, for example, a study in which patient
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Statistical Methodology, 2014
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Datta, Jyotishka, Ghosh, Jayanta K.
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Datta, Jyotishka, Ghosh, Jayanta K.
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Bootstrap and Wild Bootstrap for High Dimensional Linear Models
Annals of Statistics, 1993 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Enno Mammen
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Biometrika, 1992
Summary: For a given statistic, nested bootstrap calculations in conjunction with kernel smoothing methods are used to calculate estimates of the density of the statistic for a range of parameter values. These density estimates are then used to generate values of an analogue of a likelihood function, a whole function being obtained by curve-fitting ...
Davison, A. C. +2 more
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Summary: For a given statistic, nested bootstrap calculations in conjunction with kernel smoothing methods are used to calculate estimates of the density of the statistic for a range of parameter values. These density estimates are then used to generate values of an analogue of a likelihood function, a whole function being obtained by curve-fitting ...
Davison, A. C. +2 more
openaire +2 more sources