qci_coverage_one_sim: Computing the coverage of different confidence interval...

In hoehleatsu/quantileCI: Confidence Intervals for Quantiles

Description

Computing the coverage of different confidence interval methods for quantiles by Monte Carlo integration.

Usage

qci_coverage_one_sim(
  qci_fun,
  n,
  rfunc = rnorm,
  qfunc = qnorm,
  p = 0.5,
  conf.level = 0.95,
  ...
)

Arguments

qci_fun	Function which given n, p and conf.level computed a set of different confidence intervals. Should return a matrix of dimension 2 x (no. of methods) which contains the lower and upper bound of each confidence interval method.
n	Size of the sample to generate in the simulation
rfunc	Function for generating the samples
qfunc	Quantile function for computing the true quantile
p	The quantile of interest 0 <= p <= 1
conf.level	conf.level * 100% two-sided confidence intervals are computed
...	Additional arguments passed to rfunc and qfunc

Value

A vector of Booleans of length (no. methods) stating if each method contains the true value or not

Examples

##Function to compute different methods on same x.
quantile_confints <- function(x, p, conf.level, x_is_sorted=FALSE) {
  if (!x_is_sorted) { x <- sort(x)}

  ##Compute the various confidence intervals as above
  res <- data.frame(
    nyblom_exact=quantileCI::quantile_confint_nyblom(x=x, p=p, conf.level=conf.level,
                                                 x_is_sorted=TRUE, interpolate=FALSE),
    nyblom_interp=quantileCI::quantile_confint_nyblom(x=x, p=p, conf.level=conf.level,
                                                 x_is_sorted=TRUE, interpolate=TRUE),
    boot=quantileCI::quantile_confint_boot(x, p=p, conf.level=conf.level, R=999)
  )
  if (p == 0.5) {
    res$hs_interp = quantileCI::median_confint_hs(x=x, conf.level=conf.level,
                                                 x_is_sorted=TRUE, interpolate=TRUE)
  }
  return(res)
}

## One run of the simulation function
quantileCI::qci_coverage_one_sim(qci_fun=quantile_confints, n=100,p=0.5,conf.level=0.95)

## Several runs, calculate row means to get coverage by sampling
res <- sapply(1L:10L, function(i) {
  quantileCI::qci_coverage_one_sim(qci_fun=quantile_confints, n=100,p=0.5,conf.level=0.95)
})
res

hoehleatsu/quantileCI documentation built on Aug. 29, 2021, 4:33 a.m.