README.md

In hoehleatsu/quantileCI: Confidence Intervals for Quantiles

quantileCI

Compute confidence intervals for quantiles in the one-sample situation.

Installing the package

The R package can be installed directly from github as follows:

devtools::install_github("hoehleatsu/quantileCI")

If you have problems installing from sources: package binaries are also available from my r-universe and can be installed using:

options(repos = c(
    hoehleatsu = 'https://hoehleatsu.r-universe.dev',
    CRAN = 'https://cloud.r-project.org'))

# Install some packages
install.packages('quantileCI')

Examples

Here is a minimal working example on how to use the package once it is installed:

require(quantileCI)
x <- rnorm(25)
#Compute 25% quantile as inverse of ECDF (i.e. type=1)
quantile(x, prob=0.25, type=1)
#Compute confidence interval for it (two methods)
quantileCI::quantile_confint_exact(x=x, p=0.25, conf.level=0.95)
quantileCI::quantile_confint_nyblom(x=x, p=0.25, conf.level=0.95)

...and here is the package applied to some actual data, i.e. monitoring data from the Flint Water System. Altogether, we want a 90% CI such that the CI consists of two one-sided tests each done at the 5% significance level.

require(quantileCI)
data(flint)
#Compute type=5 quantile as in https://www.youtube.com/watch?v=9pql00zr700
quantile(flint$lead, probs=0.9, type=5)
##Compute type=1
quantile(flint$lead, probs=0.9, type=1)
##Compute corresponding non-parametric 90% CI
quantileCI::quantile_confint_exact(flint$lead, p=0.9, conf.level=0.9)

A more comprehensive treatment of the package is available as part of the blog post Better confidence intervals for quantiles.

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