R package bootstrap. bootstrap: Functions for the Book ”An Introduction to the Bootstrap”. Software (bootstrap, cross-validation, jackknife) and data for the book ”An Introduction to the Bootstrap” by B. Efron and R. Tibshirani, 1993, Chapman and Hall. This package is primarily provided for projects already based on it, and for support of the book. New projects should preferentially use the recommended package ”boot”.

References in zbMATH (referenced in 1067 articles , 1 standard article )

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  1. Zhilova, Mayya: Nonclassical Berry-Esseen inequalities and accuracy of the bootstrap (2020)
  2. Ahmad, Wan Muhamad Amir W.; Zafakali, Nursyabiha; Aleng, Nor Azlida; Ibrahim, Mohd Shafiq; Hasan, Ruhaya; Mokhtar, Kasypi: Modified zero inflated Poisson regression analysis and its application to public health data (2019)
  3. Baíllo, Amparo; Cárcamo, Javier; Getman, Konstantin: New distance measures for classifying X-ray astronomy data into stellar classes (2019)
  4. Bantis, Leonidas E.; Nakas, Christos T.; Reiser, Benjamin: Construction of confidence intervals for the maximum of the youden index and the corresponding cutoff point of a continuous biomarker (2019)
  5. Bigot, Jérémie; Cazelles, Elsa; Papadakis, Nicolas: Central limit theorems for entropy-regularized optimal transport on finite spaces and statistical applications (2019)
  6. Böhning, Dankmar; van der Heijden, Peter G. M.: The identity of the zero-truncated, one-inflated likelihood and the zero-one-truncated likelihood for general count densities with an application to drink-driving in Britain (2019)
  7. Borges, Patrick; Godoi, Luciana G.: Pólya-Aeppli regression model for overdispersed count data (2019)
  8. Boullé, Marc; Charnay, Clément; Lachiche, Nicolas: A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data (2019)
  9. Bourel, Mathias; Cugliari, Jairo: Bagging of density estimators (2019)
  10. Brazzale, Alessandra R.; Küchenhoff, Helmut; Krügel, Stefanie; Schiergens, Tobias S.; Trentzsch, Heiko; Hartl, Wolfgang: Nonparametric change point estimation for survival distributions with a partially constant hazard rate (2019)
  11. Briol, François-Xavier; Oates, Chris J.; Girolami, Mark; Osborne, Michael A.; Sejdinovic, Dino: Probabilistic integration: a role in statistical computation? (2019)
  12. Buja, Andreas; Brown, Lawrence; Berk, Richard; George, Edward; Pitkin, Emil; Traskin, Mikhail; Zhang, Kai; Zhao, Linda: Models as approximations. I. Consequences illustrated with linear regression (2019)
  13. Buja, Andreas; Brown, Lawrence; Kuchibhotla, Arun Kumar; Berk, Richard; George, Edward; Zhao, Linda: Models as approximations. II. A model-free theory of parametric regression (2019)
  14. Calabrese, Raffaella; Osmetti, Silvia Angela: A new approach to measure systemic risk: a bivariate copula model for dependent censored data (2019)
  15. Capanu, Marinela: A unified approach to proving parametric bootstrap consistency for some goodness-of-fit tests (2019)
  16. Chen, Yichao; Pun, Chi Seng: A bootstrap-based KPSS test for functional time series (2019)
  17. del Rosario, Zachary; Lee, Minyong; Iaccarino, Gianluca: Lurking variable detection via dimensional analysis (2019)
  18. Di Caterina, Claudia; Kosmidis, Ioannis: Location-adjusted Wald statistics for scalar parameters (2019)
  19. Donovan, Kevin M.; Hudgens, Michael G.; Gilbert, Peter B.: Nonparametric inference for immune response thresholds of risk in vaccine studies (2019)
  20. El-Raheem, A. M. Abd: Inference and optimal design of multiple constant-stress testing for generalized half-normal distribution under type-II progressive censoring (2019)

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