The LAG function computes one or more lagged (shifted) values for time series data. The arguments are as follows:
- x
-
specifies an
numerical matrix of time series data.
- lags
-
specifies integer lags. The lags argument can be an integer matrix with
elements. If so, the LAG function returns an 
matrix where the 
th column represents the 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;