confintr (version 0.1.0)

ci_quantile_diff: Confidence Interval for the Population Quantile Difference of two Samples

Description

This function calculates bootstrap confidence intervals for the population value of q quantile(x) - q quantile(y).

Usage

ci_quantile_diff(
  x,
  y,
  q = 0.5,
  probs = c(0.025, 0.975),
  type = "bootstrap",
  boot_type = c("bca", "perc", "norm", "basic"),
  R = 9999,
  seed = NULL,
  ...
)

Arguments

x

A numeric vector.

y

A numeric vector.

q

A single probability value determining the quantile. Set to 0.5 for the median (default).

probs

Error probabilites. The default c(0.025, 0.975) gives a symmetric 95% confidence interval.

type

Type of confidence interval. Currently, "bootstrap" is the only option.

boot_type

Type of bootstrap confidence interval ("bca", "perc", "norm", "basic").

R

The number of bootstrap resamples.

seed

An integer random seed.

...

Further arguments passed to boot::boot.

Value

A list with class cint containing these components:

• parameter: The parameter in question.

• interval: The confidence interval for the parameter.

• estimate: The estimate for the parameter.

• probs: A vector of error probabilities.

• type: The type of the interval.

• info: An additional description text for the interval.

Details

Bootstrap confidence intervals are calculated by the package "boot". The default bootstrap type is "bca" (bias-corrected & accelerated) as it enjoys the property of being second order accurate and is transformation respecting (see Efron, p. 188). The sampling is done within sample.

References

1. Efron, B. and Tibshirani R. J. (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.

2. Canty, A and Ripley B. (2019). boot: Bootstrap R (S-Plus) Functions.

See Also

ci_median_diff.

Examples

# NOT RUN {
x <- 10:30
y <- 1:30
ci_quantile_diff(x, y, R = 999)
# }