dixon.test | R Documentation |
Performs several variants of Dixon test for detecting outlier in data sample.
dixon.test(x, type = 0, opposite = FALSE, two.sided = TRUE)
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 |
two.sided |
treat test as two-sided (default). |
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).
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. |
Lukasz Komsta
Dixon, W.J. (1950). Analysis of extreme values. Ann. Math. Stat. 21, 4, 488-506.
Dixon, W.J. (1951). Ratios involving extreme values. Ann. Math. Stat. 22, 1, 68-78.
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.
chisq.out.test
, grubbs.test
set.seed(1234) x = rnorm(10) dixon.test(x) dixon.test(x,opposite=TRUE) dixon.test(x,type=10)
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