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effect -> affect

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Brian Brazil 2016-05-12 15:14:48 +01:00
parent 54de6afd22
commit 74094947ea
1 changed files with 3 additions and 3 deletions
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6
promql/functions.go
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@ -204,9 +204,9 @@ func calcTrendValue(i int, sf, tf float64, s, b, d []float64) float64 {
} }
// Holt-Winters is similar to a weighted moving average, where historical data has exponentially less influence on the current data. // 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) effects how historical data will effect the current // 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) effects // data. A lower smoothing factor increases the influence of historical data. The trend factor (0 < tf < 1) affects
// how trends in historical data will effect the current data. A higher trend factor increases the influence. // 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". // of trends. Algorithm taken from https://en.wikipedia.org/wiki/Exponential_smoothing titled: "Double exponential smoothing".
func funcHoltWinters(ev *evaluator, args Expressions) model.Value { func funcHoltWinters(ev *evaluator, args Expressions) model.Value {
mat := ev.evalMatrix(args[0]) mat := ev.evalMatrix(args[0])