An Introduction to the Bootstrap with Applications in R
the Bootstrap with. Applications in R. A. C. Davison and Diego Kuonen kuonen@statoo.com. Introduction. Bootstrap methods are resampling techniques for as-.
An Introduction to Bootstrap Methods with Applications to R
An introduction to bootstrap methods with applications to R / Michael R. Chernick Robert A. LaBudde. p. cm. Includes bibliographical references and index.
Introduction to the Bootstrap
54 Statistical Concepts and Applications in Medicine f. Aitchison and 57 An Introduction to the Bootstrap B. Efron and R. Tibshirani (1993).
Package bootstrap
Description Software (bootstrap cross-validation
An Introduction to Bootstrap
57 An Introduction to the Bootstrap B. Efron and R. Tibshirani (1993) 23.4 Application to bootstrap variance estimation.
An Introduction to Bootstrap Methods and their Application
Jan 22 2018 R ? ?. Two sources of error: statistical error because. ˆ. F = F (reduce by thought)
1 An Introduction to Statistical Learning
5.3 Lab: Cross-Validation and the Bootstrap . . . . . . . . . . . 190 G. James et al. An Introduction to Statistical Learning: with Applications in R
An Introduction to Bootstrap Methods with Applications to R
An introduction to bootstrap methods with applications to R / Michael R. Chernick Robert A. LaBudde. p. cm. Includes bibliographical references and index.
An Introduction to Statistical Learning
Gareth James • Daniela Witten •. Trevor Hastie • Robert Tibshirani. An Introduction to Statistical. Learning with Applications in R. Second Edition.
Bootstrap Methods: Recent Advances and New Applications
Michael R. Chernick 1979 there has been a flood of research on the bootstrap theory and appli- cations. ... important real world applications followed.
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