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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genepop'007: a complete re-implementation of the genepop software for Windows and Linux
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mediation: R Package for Causal Mediation Analysis
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Common Beliefs and Reality About PLS: Comments on Rönkkö and Evermann (2013)
Jörg Henseler,Jörg Henseler,Theo K. Dijkstra,Marko Sarstedt,Marko Sarstedt,Christian M. Ringle,Christian M. Ringle,Adamantios Diamantopoulos,Detmar W. Straub,David J. Ketchen,Joseph F. Hair,G. Tomas M. Hult,Roger J. Calantone +12 more
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From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation
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Bootstrap confidence intervals : when, which, what? A practical guide for medical statisticians
TL;DR: This article reviews the common algorithms for resampling and methods for constructing bootstrap confidence intervals, together with some less well known ones, highlighting their strengths and weaknesses.
References
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Book
Tensor Methods in Statistics
TL;DR: In this article, the authors provide a systematic development of tensor methods in statistics, beginning with the study of multivariate moments and cumulants, and an examination of the effect of making a polynomial transformation of the original variables.
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Theoretical Comparison of Bootstrap Confidence Intervals
TL;DR: In this article, a unified framework within which many commonly used bootstrap critical points and confidence intervals may be discussed and compared is developed, and seven different bootstrap methods are examined, each being usable in both parametric and nonparametric contexts.
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