Computers and the Theory of Statistics: Thinking the Unthinkable

By Bradley Efron. 1979

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Citations in the corpus

Mixing patterns in networks. (2002, methodology): “One way to calculate this error is to use the jackknife method [26].”
Technical trading strategies and return predictability: NYSE (2002, methodology): “18 According to Efron and Tibshirani (1986), 500 replications are chosen to be close to the true estimator. In addition, this study examines the sensitivity of these statistical inferences to the choice of 500 replications. The simulated t-values for buy, sell, and buy± sell return from 100 to 2000 ”
Accessibility of Cities in the Digital Economy (2004, methodology): “smallest for which the power-law behaviour holds.) The derivation of this formula is given in Appendix B. An error estimate for α can be derived by a standard bootstrap or jackknife resampling method [21]; for large data sets of the type discussed in this paper, a bootstrap is normally the more comp”
Resampling and Distribution of the Product Methods for Testing Indirect Effects in Complex Models (2008, methodology): “The percentile bootstrap was proposed by Efron (1979) and is described by Efron and Tibshirani (1993).”
Parameter sensitivity analysis for different complexity land surface models using multicriteria methods (2006, methodology): “To overcome the effect that specific sampling procedures may have on the outcome of the sensitivity analysis MOGSA uses bootstrapping [ Efron, 1979a, 1979b ] to determine the median (a robust statistic [Rousseeuw, 1991]) of the KS probability value.”
Analysis of Response Time Distributions (2002, background): “One approach is to estimate the standard errors of the estimates by \bootstrapping" the samples (Efron, 1979).”
To Log or Not to Log: Bootstrap as an Alternative to the Parametric Estimation of Moderation Effects in the Presence of Skewed Dependent Variables (2000, methodology): “The bootstrap is a relatively new method of empirically estimating characteristics of population distributions from sample data (Efron, 1979) that holds remarkable implications for these applied research issues.”
Surrogate data for hypothesis testing of physical systems (2018, background): “The increasing availability of powerful computing facilities has made this possible for numerical simulations [1].”
Leading innovation: Empirical evidence for ambidextrous leadership from UK high-tech SMEs (2020, methodology): “This technique provides robust estimation of sampling variances and confidence intervals (Efron, 1979).”