VUM.test | R Documentation |
Under the assumption that the data come from a Normal distribution, it performs the hypothesis testing and the confidence interval for the variance with unknown population mean.
VUM.test(x, sigma = 1, sigmasq = sigma^2,
alternative = c("two.sided", "less", "greater"), conf.level = 0.95,
...)
x |
a (non-empty) numeric vector of data values. |
sigma |
a number indicating the true value of the population standard deviation - Null hypothesis. |
sigmasq |
control argument. |
alternative |
a character string specifying the alternative hypothesis, must be one of |
conf.level |
confidence level of the interval. |
... |
further arguments to be passed to or from methods. |
A list with class "htest"
containing the following components:
statistic |
the value of the test statistic |
parameter |
the degrees of freedom for the test statistic |
p.value |
the p-value for the test. |
conf.int |
confidence interval for variance with unknown population mean associated with the specified alternative hypothesis. |
estimate |
the estimated variance. |
null.value |
the specified hypothesized value of the variance. |
alternative |
a character string describing the alternative hypothesis. |
method |
a character string indicating what type of statistical test was performed. |
data.name |
a character string giving the name of the data. |
VKM.test
, var.test
data(cars93) # Dataset provided with the package
# Variance of the maximum price (MaxPrice) assuming that the population mean
# price is unknown
VUM.test(cars93$MaxPrice, alternative="two.sided", sigma=11, conf.level=0.95)
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