Bootstrap Methods and their Application
By A. C. Davison, D. Hinkley. 1997
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Marko Sarstedt
- Dimitris Nicolas Politis
- Christian M. Ringle
- Jörg Henseler
- Joel L. Horowitz
- Victor Chernozhukov
- Joseph F. Hair
- G. Tomas M. Hult
Citations in the corpus
- Trend analysis of climate time series: A review of methods (2019, methodology): “There exist bootstrap adaptations Davison and Hinkley, 1997; Härdle, 1990) aimed at further increasing the accuracy of resampling-derived uncertainty measures.”
- Hippocampal replay of extended experience (2009, positive): “events with a Monte Carlo p-value ( Davison and Hinkley, 1997 ) < 0.01 for all shuffle types were”
- Fitting Linear Mixed-Effects Models Using lme4 (2014, methodology): “Parametric bootstrapping confidence intervals use a thin wrapper around the bootMer function that passes the results to boot.ci from the boot package (Canty and Ripley 2015; Davison and Hinkley 1997) for confidence interval calculation.”
- Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration (2012, methodology): “, bootstrapping, 10-fold or leave-one-out cross-validation) [160-162].”
- Tests of Long Memory: A Bootstrap Approach (2005, unknown): “I use an intermediate strategy, called Post-blackening Moving-Block Bootstrap that is explained in Davison and Hinkley (1997) .”
- Bootstrap Methods for Time Series (2003, background): “and Ducharme (1991), Hall (1992), Efron and Tibshirani (1993), and Davison and Hinkley (1997)”
- TEACHER'S CORNER: Structural Equation Modeling With the sem Package in R (2006, methodology): “In this example, facilities in the boot package (which is associated with Davison & Hinkley, 1997, and is part of the standard R distribution) are used to bootstrap a model fit by sem , and in my polycor package (a contributed package on CRAN) to compute polychoric correlations among ordinal…”
- Model-free model-fitting and predictive distributions (2010, background): “…to the well-known confidence interval construction; cf. Hall (1992), Efron 2If a value for θ1 is required in order to complete the calculation of a value for θ2, then a preliminary value for θ1 is obtainable from step (A). and Tibshirani (1993), Davison and Hinkley (1997), or Shao and Tu (1995).”
- Systemic Sudden Stops: The Relevance of Balance-Sheet Effects and Financial Integration (2008, unknown): “According to Davison and Hinkley (1997, pp. 100-102) , this procedure closely mimics the intra-group correlation structure of the data, due to the presence of the individual random effect.”
- Advantages of Monte Carlo Confidence Intervals for Indirect Effects (2012, methodology): “The parametric bootstrap (PB) method can be traced to Efron (1980, 1982; Efron & Tibshirani, 1986, 1993), and is sometimes called parametric simulation (Davison & Hinkley, 1997).”
- Bootstrap confidence intervals: when, which, what? A practical guide for medical statisticians. (2000, methodology): “It is interesting to note that, in practice, non-parametric simulation gives results that generally mimic the results obtained under the best "tting, not the simplest parametric model (see Hinkley, and Young in reply to Hinkley [5,8]).”