tripleEMA() function

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().

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

(Required) Number of points to average.

tables

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

Examples

The following example uses data provided by the sampledata package to show how tripleEMA() transforms data.

Calculate a three point triple exponential moving average

import "sampledata"

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