Module smooth

Module smooth 

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Moving Average Functions

Provides moving average functions. Often used to track trend, levels of support, breakouts, etc… The results are in the same scale as input data and are often used as a signal line for input data.

Enums§

MaMode
Moving average types

Functions§

alma
Arnaud Legoux Moving Average (ALMA)
dema
Double Exponential Moving Average
ewma
Exponentially Weighted Moving Average
frama
Fractal Adaptive Moving Average
fwma
Fibonacci’s Weighted Moving Average
hull
Hull’s Moving Average
hwma
Holt-Winter Moving Average
kama
Kaufman Adaptive Moving Average (KAMA)
kernel
Kernel Regression
lrf
Linear Regression Forecast (aka Time Series Forecast aka Least Squares Moving Average)
ma
Generic function to “dynamically” select moving average algorithm
mama
MESA Adaptive Moving Average
mdma
McGinley Dynamic Moving Average
pwma
Pascal’s Triangle Moving Average
sma
Simple Moving Average
ssf
Ehler’s Super Smoother Filter
t3
T3 Moving Average
tema
Triple Exponential Moving Average
trima
Triangular moving average
vidya
Volatility Index Dynamic Average (VIDYA)
vma
Variable Moving Average (VMA)
wilder
Welles Wilder’s Moving Average (aka Smoothed MA aka Running MA)
wma
Weighted Moving Average
zlma
Zero Lag moving average