Dixon Type (Q) TestsΒΆ
Local Algorithm - One-Dimensional Algorithm
Dixon Q-test algorithm uses the ratio of the gap between the possible a value outside the region of interest and the next closest value to it to the total range of the data set. This value is compared to a set of statistically determined values for a variety of confidence intervals. The basic formula is as follows:
and
where (1) is used to test whether the largest value is a value outside the region of interest, and (2) is used to test whether the smallest value in the data set of length \(N\) is a value outside the region of interest. If \(Q^{\text{test}} > Q^{\text{table}}\), the value in question is a value outside the region of interest.
Input Parameters
Parameter | Type | Constraint | Description | Remarks |
---|---|---|---|---|
\(Y\) | \(Y \in \mathbb R^N\) | \(N \in \mathbb{N}\) | Input data sequenceof length \(N\) | |
\(Q^{\text{table}}\) | A table of calculated \(Q^{\text{table}}\) values for a specific confidence level, e.g. \(90\) %, \(95\) % or \(99\) % |
Output Parameters
Parameter | Type | Constraint | Description | Remarks |
---|---|---|---|---|
\(\hat{Y}\) | \(\hat{Y} \in \mathbb R^N\) | Values in the \(Y\) list which are outside the region of interest are marked |
Single Steps using the Algorithm
References
D.B. Rorabacher, 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., vol. 63(2), pp. 139-146, 1991.
S. Walfish, A review of statistical outlier methods. Pharmaceutical Technology, 2006. Retrieved from www.pharmtech.com.