docs-v2/content/v2.0/reference/flux/stdlib/built-in/transformations/doubleema.md

title	description	aliases	menu	weight	related
doubleEMA() function	The `doubleEMA()` function calculates the exponential moving average of values grouped into `n` number of points, giving more weight to recent data at double the rate of `exponentialMovingAverage()`.	/v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/ /v2.0/reference/flux/stdlib/built-in/transformations/aggregates/doubleema/	v2_0_ref name parent doubleEMA built-in-transformations	402	/v2.0/reference/flux/stdlib/built-in/transformations/movingaverage/ /v2.0/reference/flux/stdlib/built-in/transformations/tripleema/ /v2.0/reference/flux/stdlib/built-in/transformations/timedmovingaverage/ /v2.0/reference/flux/stdlib/built-in/transformations/exponentialmovingaverage/ https://docs.influxdata.com/influxdb/latest/query_language/functions/#double-exponential-moving-average, InfluxQL DOUBLE_EXPONENTIAL_MOVING_AVERAGE()

The doubleEMA() function calculates the exponential moving average of values in the _value column grouped into n number of points, giving more weight to recent data at double the rate of exponentialMovingAverage().

Function type: Transformation

doubleEMA(n: 5)

Double exponential moving average rules

• A double exponential moving average is defined as doubleEMA = 2 * EMA_N - EMA of EMA_N.
  • EMA is an exponential moving average.
  • N = n is the period used to calculate the EMA.
• A true double exponential moving average requires at least 2 * n - 1 values. If not enough values exist to calculate the double EMA, it returns a NaN value.
• doubleEMA() inherits all exponential moving average rules.

Parameters

n

The number of points to average.

Data type: Integer

Examples

Calculate a five point double exponential moving average

from(bucket: "example-bucket"):
  |> range(start: -12h)
  |> doubleEMA(n: 5)

Function definition

doubleEMA = (n, tables=<-) =>
  tables
    |> exponentialMovingAverage(n:n)
    |> duplicate(column:"_value", as:"ema")
    |> exponentialMovingAverage(n:n)
    |> map(fn: (r) => ({r with _value: 2.0 * r.ema - r._value}))
    |> drop(columns: ["ema"])