Performs several variants of Dixon test for detecting outlier in data sample.
Usage
dixon.test(x, type = 0, opposite = FALSE, two.sided = TRUE)
Arguments
x
a numeric vector for data values.
opposite
a logical indicating whether you want to check not the value with
largest difference from the mean, but opposite (lowest, if most suspicious is highest etc.)
type
an integer specyfying the variant of test to be performed. Possible values are
compliant with these given by Dixon (1950): 10, 11, 12, 20, 21. If this value is set to zero,
a variant of the test is chosen according to sample size (10 for 3-7, 11 for 8-10, 21 for 11-13,
22 for 14 and more). The lowest or highest value is selected automatically, and can be reversed
used opposite parameter.
two.sided
treat test as two-sided (default).
Details
The p-value is calculating by interpolation using qdixon and qtable.
According to Dixon (1951) conclusions, the critical values can be obtained numerically only for n=3.
Other critical values are obtained by simulations, taken from original Dixon's paper, and
regarding corrections given by Rorabacher (1991).
Value
A list with class htest containing the following components:
statistic
the value of Dixon Q-statistic.
p.value
the p-value for the test.
alternative
a character string describing the alternative hypothesis.
method
a character string indicating what type of test was performed.
data.name
name of the data argument.
Author(s)
Lukasz Komsta
References
Dixon, W.J. (1950). Analysis of extreme values. Ann. Math. Stat. 21, 4, 488-506.
Rorabacher, D.B. (1991). Statistical Treatment for Rejection of Deviant Values: Critical Values of Dixon Q Parameter and Related Subrange Ratios at the 95 percent Confidence Level. Anal. Chem. 83, 2, 139-146.
See Also
chisq.out.test, grubbs.test
Examples
set.seed(1234)
x = rnorm(10)
dixon.test(x)
dixon.test(x,opposite=TRUE)
dixon.test(x,type=10)