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Merge pull request #15635 from prometheus/beorn7/promql 

promql: Purge Holt-Winters from a doc comment
pull/15588/head
Jan Fajerski 2024-12-11 16:24:37 +01:00 committed by GitHub
parent 8b716e3f34 ebfa1dd822
commit 9cf597c492
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1 changed files with 8 additions and 5 deletions
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13
promql/functions.go
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@ -345,11 +345,14 @@ func calcTrendValue(i int, tf, s0, s1, b float64) float64 {
return x + y
}
// Holt-Winters is similar to a weighted moving average, where historical data has exponentially less influence on the current data.
// Holt-Winter also accounts for trends in data. The smoothing factor (0 < sf < 1) affects how historical data will affect the current
// data. A lower smoothing factor increases the influence of historical data. The trend factor (0 < tf < 1) affects
// how trends in historical data will affect the current data. A higher trend factor increases the influence.
// of trends. Algorithm taken from https://en.wikipedia.org/wiki/Exponential_smoothing titled: "Double exponential smoothing".
// Double exponential smoothing is similar to a weighted moving average, where
// historical data has exponentially less influence on the current data. It also
// accounts for trends in data. The smoothing factor (0 < sf < 1) affects how
// historical data will affect the current data. A lower smoothing factor
// increases the influence of historical data. The trend factor (0 < tf < 1)
// affects how trends in historical data will affect the current data. A higher
// trend factor increases the influence. of trends. Algorithm taken from
// https://en.wikipedia.org/wiki/Exponential_smoothing .
func funcDoubleExponentialSmoothing(vals []parser.Value, args parser.Expressions, enh *EvalNodeHelper) (Vector, annotations.Annotations) {
samples := vals[0].(Matrix)[0]