This function calculates CIs for the population variance. By default, classic CIs are calculated based on the chi-squared distribution, assuming normal distribution (see Smithson). Bootstrap CIs are also available (default: "bca"). We recommend them for the non-normal case.
ci_var(
x,
probs = c(0.025, 0.975),
type = c("chi-squared", "bootstrap"),
boot_type = c("bca", "perc", "stud", "norm", "basic"),
R = 9999L,
seed = NULL,
...
)
An object of class "cint" containing these components:
parameter
: Parameter specification.
interval
: CI for the parameter.
estimate
: Parameter estimate.
probs
: Lower and upper probabilities.
type
: Type of interval.
info
: Additional description.
A numeric vector.
Lower and upper probabilities, by default c(0.025, 0.975).
Type of CI. One of "chi-squared"
(default) or
"bootstrap"
.
Type of bootstrap CI ("bca", "perc", "stud", "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()
.
The stud
(bootstrap t) bootstrap uses the standard error
of the sample variance given in Wilks.
Smithson, M. (2003). Confidence intervals. Series: Quantitative Applications in the Social Sciences. New York, NY: Sage Publications.
S.S. Wilks (1962), Mathematical Statistics, Wiley & Sons.
ci_sd
.
x <- 1:100
ci_var(x)
ci_var(x, type = "bootstrap", R = 999) # Use larger R
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