# cvCI: Confidence Intervals for Coefficient of Variation In MKmisc: Miscellaneous Functions from M. Kohl

## Description

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

## Usage

 `1` ```cvCI(x, conf.level = 0.95, method = "miller", na.rm = FALSE) ```

## Arguments

 `x` numeric vector. `conf.level` confidence level `method` character string specifing which method to use; see details. `na.rm` logical. Should missing values be removed?

## Details

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

## 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.

## Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

## 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.

`CV`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```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") ```