DescTools (version 0.99.37)

BartelsRankTest: Bartels Rank Test of Randomness

Description

Performs the Bartels rank test of randomness, which tests if a sample is sampled randomly from an underlying population. Data must at least be measured on an ordinal scale.

Usage

BartelsRankTest(x, alternative = c("two.sided", "trend", "oscillation"),
                method = c("normal", "beta", "auto"))

Arguments

x

a numeric vector containing the observations

alternative

a character string specifying the alternative hypothesis, must be one of "two.sided" (default), "trend" or "oscillation".

method

a character string specifying the method used to compute the p-value. Must be one of normal (default), beta or auto.

Value

A list with class "htest" containing the components:

statistic

the value of the normalized statistic test.

parameter, n

the size of the data, after the remotion of consecutive duplicate values.

p.value

the p-value of the test.

alternative

a character string describing the alternative hypothesis.

method

a character string indicating the test performed.

data.name

a character string giving the name of the data.

rvn

the value of the RVN statistic (not show on screen).

nm

the value of the NM statistic, the numerator of RVN (not show on screen).

mu

the mean value of the RVN statistic (not show on screen).

var

the variance of the RVN statistic (not show on screen).

Details

The RVN test statistic is $$RVN=\frac{\sum_{i=1}^{n-1}(R_i-R_{i+1})^2}{\sum_{i=1}^{n}\left(R_i-(n+1)/2\right)^2}$$ where \(R_i=rank(X_i), i=1,\dots, n\). It is known that \((RVN-2)/\sigma\) is asymptotically standard normal, where \(\sigma^2=\frac{4(n-2)(5n^2-2n-9)}{5n(n+1)(n-1)^2}\).

By using the alternative "trend" the null hypothesis of randomness is tested against a trend. By using the alternative "oscillation" the null hypothesis of randomness is tested against a systematic oscillation.

Missing values are silently removed.

Bartels test is a rank version of von Neumann's test.

References

Bartels, R. (1982) The Rank Version of von Neumann's Ratio Test for Randomness, Journal of the American Statistical Association, 77 (377), 40-46.

Gibbons, J.D. and Chakraborti, S. (2003) Nonparametric Statistical Inference, 4th ed. (pp. 97-98). URL: http://books.google.pt/books?id=dPhtioXwI9cC&lpg=PA97&ots=ZGaQCmuEUq

von Neumann, J. (1941) Distribution of the ratio of the mean square successive difference to the variance. Annals of Mathematical Statistics 12, 367-395.

See Also

rank.test, RunsTest

Examples

# NOT RUN {
## Example 5.1 in Gibbons and Chakraborti (2003), p.98.
## Annual data on total number of tourists to the United States for 1970-1982.

years <- 1970:1982
tourists <- c(12362, 12739, 13057, 13955, 14123,  15698, 17523, 18610, 19842,
      20310, 22500, 23080, 21916)
plot(years, tourists, pch=20)

BartelsRankTest(tourists, alternative="trend", method="beta")

#  Bartels Ratio Test
#
# data:  tourists
# statistic = -3.6453, n = 13, p-value = 1.21e-08
# alternative hypothesis: trend


## Example in Bartels (1982).
## Changes in stock levels for 1968-1969 to 1977-1978 (in $A million), deflated by the
## Australian gross domestic product (GDP) price index (base 1966-1967).
x <- c(528, 348, 264, -20, - 167, 575, 410, -4, 430, - 122)

BartelsRankTest(x, method="beta")
# }