tripleEMA() function

Warning! This page documents an earlier version of Flux, which is no longer actively developed. Flux v0.65 is the most recent stable version of Flux.

The tripleEMA() function calculates the exponential moving average of values in the _value column grouped into n number of points, giving more weight to recent data with less lag than exponentialMovingAverage() and doubleEMA().

Function type: Aggregate

tripleEMA(n: 5)
Triple exponential moving average rules:
  • A triple exponential moving average is defined as tripleEMA = (3 * EMA_1) - (3 * EMA_2) + EMA_3.
    • EMA_1 is the exponential moving average of the original data.
    • EMA_2 is the exponential moving average of EMA_1.
    • EMA_3 is the exponential moving average of EMA_2.
  • A true triple exponential moving average requires at least requires at least 3 * n - 2 values. If not enough values exist to calculate the triple EMA, it returns a NaN value.
  • tripleEMA() inherits all exponential moving average rules.

Parameters

n

The number of points to average.

Data type: Integer

Examples

Calculate a five point triple exponential moving average

from(bucket: "telegraf/autogen"):
  |> range(start: -12h)
  |> tripleEMA(n: 5)

Function definition

tripleEMA = (n, tables=<-) =>
	tables
		|> exponentialMovingAverage(n:n)
		|> duplicate(column:"_value", as:"ema1")
    |> exponentialMovingAverage(n:n)
		|> duplicate(column:"_value", as:"ema2")
		|> exponentialMovingAverage(n:n)
		|> map(fn: (r) => ({r with _value: 3.0 * r.ema1 - 3.0 * r.ema2 + r._value}))
		|> drop(columns: ["ema1", "ema2"])

TRIPLE_EXPONENTIAL_MOVING_AVERAGE