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Package 'bootstrap'
Description Software (bootstrap cross-validation
bootstrap
R pour les débutants
méthodes de ré-échantillonnage et de bootstrap class méthodes de classification installed.packages ou download.packages. Il est utile également de taper.
Paradis rdebuts fr
Package 'bootstrap"
October 12, 2022
Version2019.6
Date2019-06-15
TitleFunctions for the Book ``An Introduction to the Bootstrap"" AuthorS original, from StatLib, by Rob Tibshirani. R port byFriedrich Leisch.
MaintainerScott KostyshakDependsstats, R (>= 2.10.0)
LazyDataTRUE
DescriptionSoftware (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"".LicenseBSD_3_clause + file LICENSE
URLhttps://gitlab.com/scottkosty/bootstrap
BugReportshttps://gitlab.com/scottkosty/bootstrap/issuesNeedsCompilationyes
RepositoryCRAN
Date/Publication2019-06-17 09:40:08 UTC
Rtopics documented:
abcnon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 abcpar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 bcanon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 bootpred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 bootstrap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 boott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 cholost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 12abcnon
crossval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 hormone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 jackknife . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 law82 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 lutenhorm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 mouse.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 mouse.t . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21patch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Rainfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
scor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
spatial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
stamp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
tooth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Index28abcnonNonparametric ABC Confidence LimitsDescription 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
xthe data. Must be either a vector, or a matrix whose rows are the observations ttfunction defining the parameter in the resampling formtt(p,x), wherepis the vector of proportions andxis the data epsilonoptional argument specifying step size for finite difference calculations alphaoptional argument specifying confidence levels desired Value list with following components limitsThe estimated confidence points, from the ABC and standard normal methods statslist consisting oft0=observed value oftt,sighat=infinitesimal jackknife esti- mate of standard error oftt,bhat=estimated bias constantslist consisting ofa=acceleration constant,z0=bias adjustment,cq=curvature component abcpar3 tt.infapproximate influence components oftt ppmatrix whose rows are the resampling points in the least favourable family. The abc confidence points are the functionttevaluated at these points callThe deparsed callReferences
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, NewYork, London.
Examples
# compute abc intervals for the mean x <- rnorm(10) theta <- function(p,x) {sum(p*x)/sum(p)} results <- abcnon(x, theta) # compute abc intervals for the correlation x <- matrix(rnorm(20),ncol=2) theta <- function(p, x) x1m <- sum(p * x[, 1])/sum(p) x2m <- sum(p * x[, 2])/sum(p) num <- sum(p * (x[, 1] - x1m) * (x[, 2] - x2m)) den <- sqrt(sum(p * (x[, 1] - x1m)^2) *Package 'bootstrap"
October 12, 2022
Version2019.6
Date2019-06-15
TitleFunctions for the Book ``An Introduction to the Bootstrap"" AuthorS original, from StatLib, by Rob Tibshirani. R port byFriedrich Leisch.
MaintainerScott KostyshakDependsstats, R (>= 2.10.0)
LazyDataTRUE
DescriptionSoftware (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"".LicenseBSD_3_clause + file LICENSE
URLhttps://gitlab.com/scottkosty/bootstrap
BugReportshttps://gitlab.com/scottkosty/bootstrap/issuesNeedsCompilationyes
RepositoryCRAN
Date/Publication2019-06-17 09:40:08 UTC
Rtopics documented:
abcnon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 abcpar . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 bcanon . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 bootpred . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 bootstrap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 boott . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 cell . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 cholost . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 12abcnon
crossval . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 diabetes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 hormone . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 jackknife . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 law . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 law82 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 lutenhorm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 mouse.c . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 mouse.t . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21patch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Rainfall . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
scor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 23
spatial . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
stamp . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
tooth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
Index28abcnonNonparametric ABC Confidence LimitsDescription 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))