MKinfer (version 1.2)

cvCI: Confidence Intervals for Coefficient of Variation

Description

This function can be used to compute confidence intervals for the (classical) coefficient of variation.

Usage

cvCI(x, conf.level = 0.95, method = "miller", R = 9999, 
     bootci.type = c("norm", "basic", "perc", "bca"), na.rm = FALSE,
     alternative = c("two.sided", "less", "greater"), ...)

Value

A list with class "confint" containing the following components:

estimate

the estimated coefficient of variation.

conf.int

a confidence interval for the coefficient of variation.

Arguments

x

numeric vector with positive numbers.

conf.level

confidence level

method

character string specifing which method to use; see details.

R

number of bootstrap replicates; see details.

bootci.type

type of bootstrap interval; see boot.ci. Type "student" does not work.

na.rm

logical. Should missing values be removed?

alternative

a character string specifying one- or two-sided confidence intervals. Must be one of "two.sided" (default), "greater" or "less" (one-sided intervals). You can specify just the initial letter.

...

further arguments passed to function boot, e.g. for parallel computing.

Author

Matthias Kohl

Details

For details about the confidence intervals we refer to Gulhar et al (2012) and Arachchige et al (2019).

In case of bootstrap intervals type "student" does not work, since no standard error of CV is provided.

References

C.N.P.G. Arachchige, L.A. Prendergast and R.G. Staudte (2019). Robust analogues to the Coefficient of Variation. https://arxiv.org/abs/1907.01110.

M. Gulhar, G. Kibria, A. Albatineh, N.U. Ahmed (2012). A comparison of some confidence intervals for estimating the population coefficient of variation: a simulation study. Sort, 36(1), 45-69.

See Also

CV, boot.ci

Examples

x <- rnorm(100, mean = 10, sd = 2) # CV = 0.2
cvCI(x, method = "miller")
cvCI(x, method = "sharma")
cvCI(x, method = "curto")
cvCI(x, method = "mckay")
cvCI(x, method = "vangel")
cvCI(x, method = "panichkitkosolkul")
cvCI(x, method = "medmiller")
cvCI(x, method = "medmckay")
cvCI(x, method = "medvangel")
cvCI(x, method = "medcurto")
cvCI(x, method = "gulhar")
cvCI(x, method = "boot", R = 999) # R = 999 to reduce computation time for R checks

## one-sided
cvCI(x, alternative = "less")
cvCI(x, alternative = "greater")
cvCI(x, method = "boot", bootci.type = "bca", alternative = "less", R = 999)

# \donttest{
## parallel computing for bootstrap
cvCI(x, method = "boot", R = 9999, parallel = "multicore", ncpus = 2)
# }