ci_var | R Documentation |
This function calculates confidence intervals for the population variance. By default, classic confidence intervals are calculated based on the chi-squared distribution, assuming normal distribution (see Smithson). Bootstrap confidence intervals are also available and are recommended for the non-normal case as the chi-squared confidence intervals are sensitive to deviations from normality.
ci_var( x, probs = c(0.025, 0.975), type = c("chi-squared", "bootstrap"), boot_type = c("bca", "perc", "stud", "norm", "basic"), R = 9999, seed = NULL, ... )
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. One of "chi-squared" (default) or "bootstrap". |
boot_type |
Type of bootstrap confidence interval ("bca", "perc", "stud", "norm", "basic"). Only used for |
R |
The number of bootstrap resamples. Only used for |
seed |
An integer random seed. Only used for |
... |
Further arguments passed to |
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). The "stud" (bootstrap t) bootstrap uses a general formula for the standard error of the sample variance given in Wilks.
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.
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.
Efron, B. and Tibshirani R. J. (1994). An Introduction to the Bootstrap. Chapman & Hall/CRC.
Canty, A and Ripley B. (2019). boot: Bootstrap R (S-Plus) Functions.
ci_sd
.
x <- 1:100 ci_var(x) ci_var(x, type = "bootstrap", R = 999)
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