Distribution Analysis: Outlier Detection

The Method Tab

You can use the Method tab to specify the following options for estimating the location and scale parameters for the data, and for specifying the scale multiple. The Method tab is shown in Figure 17.3.

Location estimate
lists statistics used to estimate the location parameter for the data. Each statistic is described in the "Details" section of the UNIVARIATE procedure documentation in the SAS/STAT User's Guide. The statistics are as follows:
Mean
estimates the location parameter by using the mean of the data. ( Caution: The mean is not a robust statistic; it is influenced by outliers.)
Median
estimates the location parameter by using the median of the data.
Trimmed mean
estimates the location parameter by using the trimmed mean of the data.
Winsorized mean
estimates the location parameter by using the Winsorized mean of the data.
Trimmed/Winsorized cutoff
specifies the number of observations or proportion of observations used to estimate a trimmed or Winsorized mean.
Scale estimate
lists the statistics for estimating the scale parameter for the (uncontaminated) data. The statistics are as follows:
Standard deviation
estimates the scale parameter by using the standard deviation of the data. ( Caution: The standard deviation is not a robust statistic; it is influenced by outliers.)
MAD
estimates the scale parameter by using 1.4826 times the median absolute deviation from the median of the data.
Sn
estimates the scale parameter by using a constant times the robust statistic s_n of the data.
Qn
estimates the scale parameter by using a constant times the robust statistic q_n of the data.
Interquartile range
estimates the scale parameter by using the interquartile range of the data divided by 1.34898.
Gini's mean difference
estimates the scale parameter by using \sqrt{\pi}/2 times Gini's mean difference.
Scale multiplier
specifies the constant used to multiply the scale estimate. The resulting product, d, determines outliers: all values whose distance to the location estimate is greater than d are labeled as outliers.
Previous Page | Next Page | Top of Page