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
More filters
Proceedings ArticleDOI
How to avoid building DataBlades(R) that know the value of everything and the cost of nothing
TL;DR: Extensions of the generalized search tree, or GiST, to support a higher level but less type-specific approach to query selectivity estimation are discussed and results from an experimental comparison of these methods with several estimators from the literature are presented.
Journal ArticleDOI
Nonparametric estimation of benchmark doses in environmental risk assessment.
TL;DR: This work applies a nonparametric approach for calculating benchmark doses, based on an isotonic regression method for dose-response estimation with quantal-response data (Bhattacharya and Kong, 2007), and determines the large-sample properties of the estimator, develops bootstrap-based confidence limits on the BMDs, and explores the confidence limits' small- sample properties via a short simulation study.
Journal ArticleDOI
Genomic and phenotypic evolution of Escherichia coli in a novel citrate-only resource environment.
Zachary D. Blount,Rohan Maddamsetti,Nkrumah A. Grant,Sumaya T Ahmed,Tanush Jagdish,Jessica A Baxter,Brooke A. Sommerfeld,Alice Tillman,Jeremy P. Moore,Joan L. Slonczewski,Jeffrey E. Barrick,Richard E. Lenski +11 more
TL;DR: This work founded two sets of Cit+ populations and evolved them for 2500 generations in DM0 or DM25 and found evidence of substantial cell death in Cit+ clones, suggesting a recalcitrant mismatch between E. coli physiology and growth on citrate.
Journal ArticleDOI
Left-handedness is associated with greater fighting success in humans
TL;DR: Over 13,800 professional boxers and mixed martial artists of varying abilities are studied in three of the largest samples to test the fighting hypothesis, finding robust evidence that left-handed fighters have greater fighting success.
Posted Content
Comparison of the h-index for Different Fields of Research Using Bootstrap Methodology
TL;DR: The non-parametric bootstrap technique is applied for constructing confidence intervals for the h-index for different fields of research and seems to be rather satisfactory as revealed by the performed simulation.
References
More filters
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.
Journal ArticleDOI
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.