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. Fan, Rui; Lee, Ji Hyung: Predictive quantile regressions under persistence and conditional heteroskedasticity (2019)
  2. Guerrier, Stéphane; Dupuis-Lozeron, Elise; Ma, Yanyuan; Victoria-Feser, Maria-Pia: Simulation-based bias correction methods for complex models (2019)
  3. Hashimoto, Elizabeth M.; Ortega, Edwin M. M.; Cordeiro, Gauss M.; Cancho, Vicente G.; Klauberg, Carine: Zero-spiked regression models generated by gamma random variables with application in the resin oil production (2019)
  4. Hodara, P.; Reynaud-Bouret, P.: Exponential inequality for chaos based on sampling without replacement (2019)
  5. Jantakoon, N.; Volodin, A.: Interval estimation for the shape and scale parameters of the Birnbaum-Saunders distribution (2019)
  6. Jin, Ling Hui; Liu, Yan Yan; Wu, Lang: Weighted least squares method for the accelerated failure time model with auxiliary covariates (2019)
  7. Kohrs, Hendrik; Mühlichen, Hermann; Auer, Benjamin R.; Schuhmacher, Frank: Pricing and risk of swing contracts in natural gas markets (2019)
  8. Lin, Chien-Tai; Hsu, Yao-Yu; Lee, Siao-Yu; Balakrishnan, N.: Inference on constant stress accelerated life tests for log-location-scale lifetime distributions with type-I hybrid censoring (2019)
  9. Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei: Information matrix estimation procedures for cognitive diagnostic models (2019)
  10. Lledó, Josep; Pavía, Jose M.; Morillas-Jurado, Francisco G.: Incorporating big microdata in life table construction: A hypothesis-free estimator (2019)
  11. Lu, Shan: Testing the predictive ability of corridor implied volatility under GARCH models (2019)
  12. Montoya, José A.; Díaz-Francés, Eloísa; Gudelia, Figueroa P.: Estimation of the reliability parameter for three-parameter Weibull models (2019)
  13. Nguyen, Van Cuong; Ng, Chi Tim: Removing the singularity of a penalty via thresholding function matching (2019)
  14. O’Hagan, Adrian; Murphy, Thomas Brendan; Scrucca, Luca; Gormley, Isobel Claire: Investigation of parameter uncertainty in clustering using a Gaussian mixture model via jackknife, bootstrap and weighted likelihood bootstrap (2019)
  15. Owen, Art B.: Comment: unreasonable effectiveness of Monte Carlo (2019)
  16. Patel, Lekha; Gustafsson, Nils; Lin, Yu; Ober, Raimund; Henriques, Ricardo; Cohen, Edward: A hidden Markov model approach to characterizing the photo-switching behavior of fluorophores (2019)
  17. Pavía, Jose M.; Morillas, Francisco G.; Bosch-Rodríguez, Juan Carlos: Using parametric bootstrap to introduce and manage uncertainty: replicated loaded insurance life tables (2019)
  18. Rossini, Jacopo; Canale, Antonio: Quantifying prediction uncertainty for functional-and-scalar to functional autoregressive models under shape constraints (2019)
  19. Rostamian, S.; Nematollahi, N.: Estimation of stress-strength reliability in the inverse Gaussian distribution under progressively type II censored data (2019)
  20. Shen, Changyu; Xu, Huiping: Randomized phase III oncology trials: a survey and empirical Bayes inference (2019)

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