`ma`

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

## 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.