This function calculates confidence intervals for a population quantile. By default, distribution-free confidence intervals based on the binomial distribution are formed, see Hahn and Meeker. Alternatively, bootstrap confidence intervals are available.
ci_quantile(
x,
q = 0.5,
probs = c(0.025, 0.975),
type = c("binomial", "bootstrap"),
boot_type = c("bca", "perc", "norm", "basic"),
R = 9999,
seed = NULL,
...
)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.
A numeric vector.
A single probability value determining the quantile. Set to 0.5 for the median (the default).
Error probabilites. The default c(0.025, 0.975) gives a symmetric 95% confidence interval.
Type of confidence interval. One of "binomial" (default), or "bootstrap".
Type of bootstrap confidence interval ("bca", "perc", "norm", "basic"). Only used for type = "bootstrap".
The number of bootstrap resamples. Only used for type = "bootstrap".
An integer random seed. Only used for type = "bootstrap".
Further arguments passed to boot::boot.
Bootstrap confidence intervals are calculated by the package "boot", see references. The default bootstrap type is "bca" (bias-corrected accelerated) as it enjoys the property of being second order accurate as well as transformation respecting (see Efron, p. 188).
Hahn, G. and Meeker, W. (1991). Statistical Intervals. Wiley 1991.
Efron, B. and Tibshirani R. J. (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.
Canty, A and Ripley B. (2019). boot: Bootstrap R (S-Plus) Functions.
ci_quantile.
x <- 1:100
ci_quantile(x)
ci_quantile(x, q = 0.25)
ci_quantile(x, q = 0.25, type = "bootstrap", R = 999)
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