`ma`

computes a simple moving average smoother of a given time series.

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 for even orders. |

## Value

Numerical time series object containing the simple moving average
smoothed values.

## Details

The moving average smoother averages the nearest `order`

periods of
each observation. As neighbouring observations of a time series are likely
to be similar in value, averaging eliminates some of the randomness in the
data, leaving a smooth trend-cycle component. $$\hat{T}_{t} =
\frac{1}{m} \sum_{j=-k}^k
y_{t+j}$$ where
\(k=\frac{m-1}{2}\)

When an even `order`

is specified, the observations averaged will
include one more observation from the future than the past (k is rounded
up). If centre is TRUE, the value from two moving averages (where k is
rounded up and down respectively) are averaged, centering the moving
average.

## See also

`decompose`

## Examples

plot(wineind)

sm <- ma(wineind,order=12)
lines(sm,col="red")