Bootstrap Confidence Intervals
Thomas J. DiCiccio,Bradley Efron +1 more
TLDR
Bootstrap methods for estimating confidence intervals have been surveyed in this article, with a focus on improving the accuracy of the standard confidence intervals in a way that allows routine application even to very complicated problems.Abstract:
This article surveys bootstrap methods for producing good approximate confidence intervals. The goal is to improve by an order of magnitude upon the accuracy of the standard intervals $\hat{\theta} \pm z^{(\alpha)} \hat{\sigma}$, in a way that allows routine application even to very complicated problems. Both theory and examples are used to show how this is done. The first seven sections provide a heuristic overview of four bootstrap confidence interval procedures: $BC_a$, bootstrap-t , ABC and calibration. Sections 8 and 9 describe the theory behind these methods, and their close connection with the likelihood-based confidence interval theory developed by Barndorff-Nielsen, Cox and Reid and others.read more
Citations
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Normality of residuals is a continuous variable, and does seem to influence the trustworthiness of confidence intervals : A response to, and appreciation of, Williams, Grajales, and Kurkiewicz (2013)
TL;DR: In a follow-up paper as discussed by the authors, the authors pointed out that researchers often do not check on or report on the assumptions of their statistical methods, and advocated a thorough examination of data prior to reporting results, and provided an example of how incremental improvements in meeting the assumption of normality of residuals incrementally improves the accuracy of confidence intervals.
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Psychologists Should Use Brunner-Munzel’s Instead of Mann-Whitney’s U Test as the Default Nonparametric Procedure:
TL;DR: In some situations, the parametric t test is inappropriate, and a non-parametric t-test is more appropriate as mentioned in this paper, which is the standard procedure in many situations.
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Evaluating Performance of Photographs for Marine Citizen Science Applications
TL;DR: In this paper, the authors compare measurement methods used to document community structure and assess changes in marine systems, and explore potential applications in citizen science, concluding that live measurements were more accurate and better represented these marine communities, having higher richness and diversity measurements than photographic measurements.
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Emissions of organic compounds from produced water ponds III: Mass-transfer coefficients, composition-emission correlations, and contributions to regional emissions.
TL;DR: Analysis of data on the concentration of organic compounds in the water and on the flux of the same compounds into the atmosphere suggests partitioning between hydrocarbons in aqueous solution and in suspension, especially at higher overall concentrations.
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Bootstrap-based confidence interval estimation for thermal security region of bulk power grid
TL;DR: In this article, a bootstrap based confidence interval estimation is proposed to estimate not only the coefficients of TSRB approximation hyperplane, but also the standard deviations and confidence intervals of the coefficients for evaluating the quality and reliability of the approximation results.
References
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Book
An introduction to the bootstrap
Bradley Efron,Robert Tibshirani +1 more
TL;DR: This article presents bootstrap methods for estimation, using simple arguments, with Minitab macros for implementing these methods, as well as some examples of how these methods could be used for estimation purposes.
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Bootstrap Methods: Another Look at the Jackknife
TL;DR: In this article, the authors discuss the problem of estimating the sampling distribution of a pre-specified random variable R(X, F) on the basis of the observed data x.
Book
Bootstrap Methods and Their Application
Anthony C. Davison,David Hinkley +1 more
TL;DR: In this paper, a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis, is given, along with a disk of purpose-written S-Plus programs for implementing the methods described in the text.
Journal ArticleDOI
Better Bootstrap Confidence Intervals
TL;DR: In this article, the authors consider the problem of setting approximate confidence intervals for a single parameter θ in a multiparameter family, and propose a method to automatically incorporate transformations, bias corrections, and so on.
Beiter Bootstrap Confidence Intervals
TL;DR: In this article, the authors consider the problem of setting approximate confidence intervals for a single parameter 0 in a multiparameter family, and propose the bootstrap confidence intervals that automatically incorporate transformations, bias corrections, and so forth.