The R6 class CoefVarCI
for the confidence intervals of
coefficient of variation (cv)
An R
object. Currently there are methods for numeric vectors
a logical value indicating whether NA
values should be
stripped before the computation proceeds.
integer indicating the number of decimal places to be used.
a scalar representing the type of confidence intervals required. The value should be any of the values "kelley_ci", "mckay_ci", "miller_ci", "vangel_ci", "mahmoudvand_hassani_ci", "equal_tailed_ci", "shortest_length_ci", "normal_approximation_ci", "norm_ci","basic_ci", or "all_ci".
The allowed type I error probability
integer indicating the number of bootstrap replicates.
returns the unbiased estimate of the coefficient of variation if TRUE is determined.
An object of type "list" which contains the estimate, the intervals, and the computation method. It has two main components:
A description of statistical method used for the computations.
A data frame representing three
vectors: est/, lower and upper limits of confidence interval (CI)
;
additional description vector is provided when "all" is selected:
est: cv*100
Kelley Confidence
Interval: Thanks to package MBESS [2]
for the
computation of confidence limits for the noncentrality parameter from a
t distribution conf.limits.nct [3]
.
McKay Confidence Interval: The intervals calculated by the method
introduced by McKay [4]
, using chi-square distribution.
Miller Confidence Interval: The intervals calculated by the
method introduced by Miller [5]
, using the standard normal
distribution. Vangel Confidence Interval: Vangel
[6]
proposed a method for the calculation of CI for cv; which
is a modification on McKay<U+2019>s CI. Mahmoudvand-Hassani
Confidence Interval: Mahmoudvand and Hassani [7]
proposed a new CI
for cv; which is obtained using ranked set sampling (RSS)
Normal Approximation Confidence Interval: Wararit
Panichkitkosolkul [8]
proposed another CI for cv; which is a
normal approximation. Shortest-Length Confidence
Interval: Wararit Panichkitkosolkul [8]
proposed another CI for
cv; which is obtained through minimizing the length of CI.
Equal-Tailed Confidence Interval: Wararit Panichkitkosolkul
[8]
proposed another CI for cv; which is obtained using
chi-square distribution. Bootstrap Confidence
Intervals: Thanks to package boot by Canty & Ripley [9]
we
can obtain bootstrap CI around cv using boot.ci.
The cv
is a measure of relative dispersion representing the degree of variability
relative to the mean [1]
. Since \(cv\) is unitless, it is useful
for comparison of variables with different units. It is also a measure of
homogeneity [1]
.
[1]
Albatineh, AN., Kibria, BM., Wilcox, ML., & Zogheib,
B, 2014, Confidence interval estimation for the population coefficient of
variation using ranked set sampling: A simulation study, Journal of Applied
Statistics, 41(4), 733<U+2013>751, DOI:
http://doi.org/10.1080/02664763.2013.847405
[2]
Kelley, K., 2018, MBESS: The MBESS R Package. R
package version 4.4. 3.
[3]
Kelley, K., 2007, Sample size planning for the
coefficient of variation from the accuracy in parameter estimation
approach, Behavior Research Methods, 39(4), 755<U+2013>766, DOI:
http://doi.org/10.3758/BF03192966
[4]
McKay, AT., 1932, Distribution of the Coefficient of
Variation and the Extended<U+201C> t<U+201D> Distribution, Journal of the Royal
Statistical Society, 95(4), 695<U+2013>698
[5]
Miller, E., 1991, Asymptotic test statistics for
coefficients of variation, Communications in Statistics-Theory and Methods,
20(10), 3351<U+2013>3363
[6]
Vangel, MG., 1996, Confidence intervals for a normal
coefficient of variation, The American Statistician, 50(1), 21<U+2013>26
[7]
Mahmoudvand, R., & Hassani, H., 2009, Two new
confidence intervals for the coefficient of variation in a normal
distribution, Journal of Applied Statistics, 36(4), 429<U+2013>442
[8]
Panichkitkosolkul, W., 2013, Confidence Intervals for
the Coefficient of Variation in a Normal Distribution with a Known
Population Mean, Journal of Probability and Statistics, 2013, 1<U+2013>11,
http://doi.org/10.1155/2013/324940
[9]
Canty, A., & Ripley, B., 2017, boot: Bootstrap R
(S-Plus) Functions, R package version 1.3-20
# NOT RUN {
y <- c(
0.2, 0.5, 1.1, 1.4, 1.8, 2.3, 2.5, 2.7, 3.5, 4.4,
4.6, 5.4, 5.4, 5.7, 5.8, 5.9, 6.0, 6.6, 7.1, 7.9
)
CoefVarCI$new(x = y)$kelley_ci()
cv_y <- CoefVarCI$new(
x = y,
alpha = 0.05,
R = 1000,
digits = 2,
correction = TRUE
)
cv_y$kelley_ci()
cv_y$mckay_ci()
R6::is.R6(cv_y)
# }
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