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This takes a bootstrap object and produces plots for the bootstrap replicates of the variable of interest.
● Data Source:
CranContrib
● Keywords: hplot, nonparametric
● Alias: plot.boot
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This is a method for the function print() for objects of the class "boot".
● Data Source:
CranContrib
● Keywords: htest, nonparametric
● Alias: print.boot
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This function calculates the empirical influence values for a statistic applied to a data set. It allows four types of calculation, namely the infinitesimal jackknife (using numerical differentiation), the usual jackknife estimates, the ‘positive’ jackknife estimates and a method which estimates the empirical influence values using regression of bootstrap replicates of the statistic. All methods can be used with one or more samples.
● Data Source:
CranContrib
● Keywords: math, nonparametric
● Alias: empinf
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Makes plot of jackknife deviance residuals against linear predictor, normal scores plots of standardized deviance residuals, plot of approximate Cook statistics against leverage/(1-leverage), and case plot of Cook statistic.
● Data Source:
CranContrib
● Keywords: dplot, hplot, regression
● Alias: glm.diag.plots
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This function calculates overall and pointwise confidence envelopes for a curve based on bootstrap replicates of the curve evaluated at a number of fixed points.
● Data Source:
CranContrib
● Keywords: dplot, htest
● Alias: envelope
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This function calculates the importance sampling weight required to correct for simulation from a distribution with probabilities p when estimates are required assuming that simulation was from an alternative distribution with probabilities q.
● Data Source:
CranContrib
● Keywords: nonparametric
● Alias: imp.weights
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boot-practicals
(Package: boot) :
Functions for Bootstrap Practicals
Functions for use with the practicals in Davison and Hinkley (1997).
● Data Source:
CranContrib
● Keywords: internal
● Alias: lik.CI, nested.corr
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This function takes a bootstrap object and for each bootstrap replicate it calculates the linear approximation to the statistic of interest for that bootstrap sample.
● Data Source:
CranContrib
● Keywords: nonparametric
● Alias: linear.approx
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Take a matrix of indices for nonparametric bootstrap resamples and return the frequencies of the original observations in each resample.
● Data Source:
CranContrib
● Keywords: nonparametric
● Alias: freq.array
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This is a method for the function print() to print objects of class "simplex".
● Data Source:
CranContrib
● Keywords: optimize, print
● Alias: print.simplex
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providing 
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