Computer-Intensive Methods in Statistics

By Persi Diaconis, Bradley Efron. 1983

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Citations in the corpus

Pylearn2: a machine learning research library (2013, methodology): “These include the datasets used for DARPA’s unsupervised and transfer learning challenge [25] , the dataset used for the NIPS 2011 workshops challenge in representation learning [32], the C IFAR-10 and CIFAR-100 datasets [29], the MNIST dataset [34], some of the MNIST variations dataset s [31], the ”
Bootstrap Resampling Approaches for Repeated Measure Designs: Relative Robustness to Sphericity and Normality Violations (2000, methodology): “This statement is reminiscent of the premise behind recent bootstrap resampling approaches attributed to Efron and colleagues (e.g., Diaconis & Efron, 1983; Efron, 1979; Efron & Gong, 1983), whereby an empirical sampling distribution for the test statistic of interest is derived by repeatedly resa”
Rainfall depth-duration-frequency curves and their uncertainties (2008, methodology): “In the bootstrap method new samples (bootstrap samples) are generated by sampling with replacement from the original sample (Diaconis and Efron, 1983; Efron and Tibshirani, 1993).”
A general regression model for lifetime evaluation and prediction (2001, methodology): “Note that since the parameter and quantile estimates are well defined for all possible combinations of parameter and sample values, the variances of these estimates (hence, confidence intervals for the corresponding parameter or quantile values) can be obtained using sampling based methods such as t”
Central Masses and Broad-Line Region Sizes of Active Galactic Nuclei. II. A Homogeneous Analysis of a Large Reverberation-Mapping Database (2004, methodology): “Thus, rather than omitting redundant points, each of the N selections has some real effect on the outcome of the realization and the weighting is more consistent with the standard bootstrap method (e.g., Diaconis & Efron 1983) on which the FR/RSS method is based.”
Cover-weighted averaging of indicator values in vegetation analyses (2004, methodology): “To correct rs for this, we performed a bootstrap analysis, consisting of 1000 repeats (Diaconis & Efron 1983; Efron & Tibshirani 1993).”
Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods (2018, methodology): “Bootstrapping (Diaconis & Efron, 1983) is the most widely used method for standard error estimation in PLS-SEM.”
Bootstrapping for multivariate linear regression models (2017, methodology): “The existence of such an extension is stated without proof and rather implicitly in subsequent works [Freedman and Peters, 1984, Diaconis and Efron, 1983].”