docs-v2/content/flux/v0.x/stdlib/universe/doubleema.md

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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()`.	/influxdb/v2.0/reference/flux/functions/built-in/transformations/aggregates/doubleema/ /influxdb/v2.0/reference/flux/stdlib/built-in/transformations/aggregates/doubleema/ /influxdb/v2.0/reference/flux/stdlib/built-in/transformations/doubleema/ /influxdb/cloud/reference/flux/stdlib/built-in/transformations/doubleema/	flux_0_x_ref name parent doubleEMA universe	102	transformations	/flux/v0.x/stdlib/universe/movingaverage/ /flux/v0.x/stdlib/universe/tripleema/ /flux/v0.x/stdlib/universe/timedmovingaverage/ /flux/v0.x/stdlib/universe/exponentialmovingaverage/ /{{< latest "influxdb" "v1" >}}/query_language/functions/#double-exponential-moving-average, InfluxQL DOUBLE_EXPONENTIAL_MOVING_AVERAGE()	0.38.0

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().

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

Number of points to average.

tables

Input data. Default is piped-forward data (<-).

Examples

{{% flux/sample-example-intro %}}

Calculate a three point double exponential moving average

import "sampledata"

sampledata.int()
    |> doubleEMA(n: 3)

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Input data

{{% flux/sample set="int" %}}

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Output data

_time	tag	_value
2021-01-01T00:00:40Z	t1	16.627222222222223
2021-01-01T00:00:50Z	t1	8.301527777777778

_time	tag	_value
2021-01-01T00:00:40Z	t2	15.907222222222224
2021-01-01T00:00:50Z	t2	5.941527777777779

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