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 1043 articles , 1 standard article )

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  1. Neumann, André; Bodnar, Taras; Dickhaus, Thorsten: Estimating the proportion of true null hypotheses under dependency: a marginal bootstrap approach (2021)
  2. Ali, Mohsin; Shah, Syed Touqeer H.; Imran, Mudassar; Khan, Adnan: The role of asymptomatic class, quarantine and isolation in the transmission of COVID-19 (2020)
  3. Andres, Jan; Langer, Jiří; Matlach, Vladimír: Fractal-based analysis of sign language (2020)
  4. Bastani, Hamsa; Bayati, Mohsen: Online decision making with high-dimensional covariates (2020)
  5. Coolen, Frank P. A.; Himd, Sulafah Bin: Nonparametric predictive inference bootstrap with application to reproducibility of the two-sample Kolmogorov-Smirnov test (2020)
  6. Franco-Pereira, Alba M.; Martínez-Camblor, Pablo: Testing ageing notions through percentiles of the residual life (2020)
  7. García-Bárzana, Marta; Ramos-Guajardo, Ana Belén; Colubi, Ana; Kontoghiorghes, Erricos J.: Multiple linear regression models for random intervals: a set arithmetic approach (2020)
  8. García-Pola, Bernardo: Do people minimize regret in strategic situations? A level-(k) comparison (2020)
  9. García-Pola, Bernardo; Iriberri, Nagore; Kovářík, Jaromír: Non-equilibrium play in centipede games (2020)
  10. Hsiao, Hsiao-Fen; Huang, Jiang-Chuan; Lin, Zheng-Wei: Portfolio construction using bootstrapping neural networks: evidence from global stock market (2020)
  11. Sadeghpour, Amineh; Salehi, Mahdi; Nezakati, Ahmad: Estimation of the stress-strength reliability using lower record ranked set sampling scheme under the generalized exponential distribution (2020)
  12. Stepien, Tracy L.; Kostelich, Eric J.; Kuang, Yang: Mathematics + cancer: an undergraduate “bridge” course in applied mathematics (2020)
  13. Wang, Haixu; Cao, Jiguo: Estimating time-varying directed neural networks (2020)
  14. 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)
  15. Baíllo, Amparo; Cárcamo, Javier; Getman, Konstantin: New distance measures for classifying X-ray astronomy data into stellar classes (2019)
  16. 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)
  17. Bigot, Jérémie; Cazelles, Elsa; Papadakis, Nicolas: Central limit theorems for entropy-regularized optimal transport on finite spaces and statistical applications (2019)
  18. 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)
  19. Boullé, Marc; Charnay, Clément; Lachiche, Nicolas: A scalable robust and automatic propositionalization approach for Bayesian classification of large mixed numerical and categorical data (2019)
  20. Bourel, Mathias; Cugliari, Jairo: Bagging of density estimators (2019)

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