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DescTools (version 0.99.18)

VarCI: Confidence Interval for the Variance

Description

Calculates the confidence interval for the variance either the classical way or with the bootstrap approach.

Usage

VarCI(x, method = c("classic", "norm", "basic", "stud", "perc", "bca"), conf.level = 0.95, sides = c("two.sided", "left", "right"), na.rm = FALSE, R = 999)

Arguments

x
a (non-empty) numeric vector of data values.

method
vector of character strings representing the type of intervals required. The value should be any subset of the values "classic", "norm", "basic", "stud", "perc", "bca". See boot.ci.

conf.level
confidence level of the interval.

sides
a character string specifying the side of the confidence interval, must be one of "two.sided" (default), "left" or "right". You can specify just the initial letter. "left" would be analogue to a hypothesis of "greater" in a t.test.
na.rm
logical. Should missing values be removed? Defaults to FALSE.

R
number of bootstrap replicates. Usually this will be a single positive integer. For importance resampling, some resamples may use one set of weights and others use a different set of weights. In this case R would be a vector of integers where each component gives the number of resamples from each of the rows of weights. See boot.

Value

See Also

MeanCI, MedianCI

Examples

Run this code
VarCI(d.pizza$price, na.rm=TRUE)
VarCI(d.pizza$price, conf.level=0.99, na.rm=TRUE)

x <- c(14.816, 14.863, 14.814, 14.998, 14.965, 14.824, 14.884, 14.838, 14.916,
       15.021, 14.874, 14.856, 14.860, 14.772, 14.980, 14.919)
VarCI(x, conf.level=0.9)

# and for the standard deviation
sqrt(VarCI(x, conf.level=0.9))

# some bootstrap intervals
VarCI(x, method="norm")
VarCI(x, method="perc")
VarCI(x, method="bca")

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