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HYBRIDTEST2


outlier gts
Since v1.0.0
Available on all platforms
See also

The HYBRIDTEST2 function detects outliers in a GTS (or a LIST of GTS) which has a seasonal part.

HYBRIDTEST2 is almost the same procedure than HYBRIDTEST except that it does not use STL decomposition for the seasonal extract.

The seasonal part is approximated by pondering each value with the entropy of the modified Z-score of its seasonal subseries (series with only the values of the same season).

This test is usually preferred when it is meaningful to think in term of entropy, for example when the GTS represents counters of events. Also as it does not use STL decomposition, it is not prone to border effects, but at the cost of not detecting slight outliers.

This function only applies to bucketized GTS of type DOUBLE.

Signature

Examples

// Macro used to generate an approximately normal distribution (using central limit theorem) <% RAND RAND RAND RAND RAND RAND + + + + + 3.0 - %> 'normal' STORE // we generate a GTS with an approximately normal distribution [ NEWGTS 1 100 <% NaN NaN NaN @normal ADDVALUE %> FOR // we add outliers 25 NaN NaN NaN -17 ADDVALUE 36 NaN NaN NaN 18 ADDVALUE 71 NaN NaN NaN 23 ADDVALUE 82 NaN NaN NaN -12 ADDVALUE DEDUP // we generate a periodic GTS of mean 0 NEWGTS 1 100 <% NaN NaN NaN 4 PICK 10 % 4.5 - ADDVALUE %> FOR // we generate a trend GTS (piecewise raise) NEWGTS 1 100 <% NaN NaN NaN 4 PICK 50 / 5 + ADDVALUE %> FOR ] // we sum up the 3 components: remainder, seasonal and trend [ SWAP [] reducer.sum ] REDUCE 'sum' RENAME // bucketize [ SWAP bucketizer.first 0 1 100 ] BUCKETIZE 0 GET // we call HYBRIDTEST2 10 5 2 HYBRIDTEST2