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ST_deandixon

Basic Dean-Dixon outlier test

Calling Sequence

[outlierfree] = ST_deandixon(v, p)
[outlierfree, outlier] = ST_deandixon(v, p)

Parameters

v:

vector of numerical values

p:

statistical confidence level (%) as a string or the level of significance (alpha) as a decimal value, "95%", "99%", "99.9%" or 0.05, 0.01, 0.001 resp (see examples).

outlierfree:

vector of outlier-free data

outlier:

vector of outliers

Description

Performs the basic Dean-Dixon outlier test. It sorts the distribution in ascending or descending order, then takes the minimum and maximum values (xi) and calculates the respective Q value for both xi values. This is compared with the critical value from a table (Qcrit). If one of the two or both Q values greater than the corresponding Qcrit value, one orboth xi values are outliers.

\begin{eqnarray} Q = \left | x_{i+1}-x_i \right |/\left | x_n-x_i \right | \quad ; \quad Q > Q_{crit} \quad \Rightarrow \quad x_i = \text{outlier} \end{eqnarray}

Only one outlier can be found on each side.

Apply this test ONLY one time to your data.

Do use ST_deandixon ONLY with NORMAL distributed data and with more than 3 and less than 30 values! For more than 30 values use Pearson-Hartley test ""ST_pearsonhartley()"" instead.

Examples

data = [6 8 14 12 35 15];
of = ST_deandixon(data, "95%")      // outlier-free values
[of, o] = ST_deandixon(data, "95%") // outlier and outlier-free values
[of, o] = ST_deandixon(data, 0.05)  // outlier and outlier-free values

See also

Authors

Bibliography

Lohringer, H., "Grundlagen der Statistik", Oct, 10th, 2012, http://www.statistics4u.info/fundstat_germ/cc_outlier_tests_4sigma.html


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