Date 2012-04-04. Title Functions for the Book ''An Introduction to the Bootstrap''.
Author S original, from StatLib, by Rob Tibshirani. R port by Friedrich Leisch.
Package ‘bootstrap’ February 27, 2017 Version 2017.2 Date 2017-02-27 Title Functions for the Book ``An Introduction to the Bootstrap'' Author S original, from StatLib, by Rob Tibshirani. R port by Friedrich Leisch. Maintainer Scott Kostyshak Depends stats, R (>= 2.10.0) LazyData TRUE Description 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''. License BSD_3_clause + file LICENSE NeedsCompilation yes Repository CRAN Date/Publication 2017-02-27 21:42:39
R topics documented: abcnon . . abcpar . . bcanon . . bootpred . bootstrap boott . . . cell . . . . cholost . . crossval . diabetes . hormone .
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abcnon jackknife law . . . . law82 . . lutenhorm mouse.c . mouse.t . patch . . . Rainfall . scor . . . spatial . . stamp . . tooth . . .
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Index abcnon
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Nonparametric ABC Confidence Limits
Description See Efron and Tibshirani (1993) for details on this function. Usage abcnon(x, tt, epsilon=0.001, alpha=c(0.025, 0.05, 0.1, 0.16, 0.84, 0.9, 0.95, 0.975)) Arguments x tt epsilon alpha
the data. Must be either a vector, or a matrix whose rows are the observations function defining the parameter in the resampling form tt(p,x), where p is the vector of proportions and x is the data optional argument specifying step size for finite difference calculations optional argument specifying confidence levels desired
Value list with following components limits stats constants tt.inf pp call
The estimated confidence points, from the ABC and standard normal methods list consisting of t0=observed value of tt, sighat=infinitesimal jackknife estimate of standard error of tt, bhat=estimated bias list consisting of a=acceleration constant, z0=bias adjustment, cq=curvature component approximate influence components of tt matrix whose rows are the resampling points in the least favourable family. The abc confidence points are the function tt evaluated at these points The deparsed call
abcpar
3
References Efron, B, and DiCiccio, T. (1992) More accurate confidence intervals in exponential families. Biometrika 79, pages 231-245. Efron, B. and Tibshirani, R. (1993) An Introduction to the Bootstrap. Chapman and Hall, New York, London. Examples # compute abc intervals for the mean x
