Add Holt-Winters to moving_avg aggregation #11043
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| tracks the seasonal aspect of your data. This aggregation therefore smooths based on three components: "level", "trend" | ||
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| The level and trend calculation is identical to `ewma` The seasonal calculation looks at the difference between |
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Shouldn't this be 'identical to the Holt-Linear'? isn't it Holt-Linear which smooths based on level and trend?
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@polyfractal left some comments but it looks pretty good |
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@colings86 All tidied up :) |
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LGTM |
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Aggregations: Add Holt-Winters model to `moving_avg` pipeline aggregation
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Adds Holt-Winters model (aka triple exponential) to
moving_avgaggregation. Holt-Winters has some finicky properties, so there were general changes to the agg to help make life easier:settingshash parsing, such that proper SearchParsePhaseExceptions are thrown if the datatype is wrong, out of bounds, etchasNext()to determine if the model is capable of producing a new value. This is important for HW, which has a "cold start" phase at the beginning where it is incapable of producing values.reduce()method