ma

0th

Percentile

Moving-average smoothing

Computes a simple moving average smoother.

Keywords
ts
Usage
ma(x, order, centre=TRUE)
Arguments
x
Univariate time series
order
Order of moving average smoother
centre
If TRUE, then the moving average is centred.
Value

• Numerical time series object containing the smoothed values.

ksmooth, decompose

• ma
Examples
plot(wineind)
sm <- ma(wineind,order=12)
lines(sm,col="red")
Documentation reproduced from package forecast, version 3.22, License: GPL (>= 2)

Community examples

twigt.arie@gmail.com at Sep 23, 2018 forecast v8.4

## Example to get an understanding how values are calculated by applying the ma() function. {r} # create a numerical vector which is easy to understand numbers <- c(3, 5, 3, 6, 4, 5, 3, 4, 4, 6, 3, 5, 4, 6, 3, 5, 4, 4, 6, 3, 5) # apply the 'ma' function ma(numbers, order = 5)  Calculate the average for the first 5 numbers by hand. {r} (sum(3, 5, 3, 6, 4))/5