ci_skewness: Confidence Interval for the Skewness

In confintr: Confidence Intervals

Description

This function calculates bootstrap confidence intervals for the population skewness, see Details.

Usage

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

Arguments

x	A numeric vector.
probs	Error probabilites. The default c(0.025, 0.975) gives a symmetric 95% confidence interval.
type	Type of confidence interval. Currently not used as the only type is "bootstrap".
boot_type	Type of bootstrap confidence interval c("bca", "perc", "norm", "basic").
R	The number of bootstrap resamples.
seed	An integer random seed.
...	Further arguments passed to boot::boot.

Details

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).

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.

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

moments, ci_kurtosis.

Examples

set.seed(1)
x <- rnorm(100)
ci_skewness(x, R = 999)

Example output

	Two-sided 95% bootstrap confidence interval for the population
	skewness based on 999 bootstrap replications and the bca method

Sample estimate: -0.0722319 
Confidence interval:
      2.5%      97.5% 
-0.4917919  0.3368046 

confintr documentation built on July 2, 2020, 1:51 a.m.