Estimates the confidence interval using the methods provided by types.
tau must be a function that calculates tau.n from its argument n.
If it is not provided, it is estimated with estimate.tau using the default settings of this function.
mboot.ci(boot.out, conf = 0.95, tau = NULL, types = "all", ...)A list of confidence intervals for the given types.
The simulated bootstrap distribution from the mboot call.
The confidence level.
Function that returns its only argument applied to tau. If NULL, estimate.tau is used to estimate tau.
The types of confidence intervals to be calculated. The value can be 'all' for all types, or a
subset of c("basic", "norm", "sherman").
When tau is omitted, the additional parameters are passed to statistic when estimating tau.
The additional parameters are passed to the statistic function if tau was omitted.
To specify the arguments of the estimate.tau, call this function directly and use its return value as tau argument.
For the type sherman, tau is not needed and is therefore not calculated.
Politis D.N. and Romano J.P. (1994) Large sample confidence regions based on subsamples under minimal assumptions The Annals of Statistics, 22(4):2031-2050, doi:10.1214/aos/1176325770.
Sherman M. and Carlstein E. (2004) Confidence intervals based on estimators with unknown rates of convergence. Computional statistics & data analysis, 46(1):123-136.
mboot estimate.tau
data <- runif(1000)
estimate.max <- function(data, indices) {return(max(data[indices]))}
tau <- \(x){x} # convergence rate
boot.out <- mboot(data, estimate.max, R = 1000, m = 2*sqrt(NROW(data)), replace = FALSE)
cis <- mboot.ci(boot.out, 0.95, tau, c("all"))
ci.basic <- cis$basic
print(ci.basic)
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