LAG Function

LAG (x <, lags> ) ;

The LAG function computes one or more lagged (shifted) values for time series data. The arguments are as follows:

x

specifies an $n\times 1$ numerical matrix of time series data.

lags

specifies integer lags. The lags argument can be an integer matrix with $d$ elements. If so, the LAG function returns an $n\times d$ matrix where the $i$th column represents the $i$th lag applied to the time series. If the lags argument is not specified, a value of 1 is used.

The values of the lags argument are usually positive integers. A positive lag shifts the time series data backwards in time. A lag of 0 represents the original time series. A negative value for the lags argument shifts the time series data forward in time; this is sometimes called a lead effect. The LAG function is related to the DIF function.

For example, the following statements compute several lags:

x = {1,3,4,7,9};
lag = lag(x, {0 1 3});
print lag;

Figure 24.182: Lagged Data

lag
1 . .
3 1 .
4 3 .
7 4 1
9 7 3