DIF Function

DIF (x <, lags> ) ;

The DIF function computes the differences between data values and one or more lagged (shifted) values for time series data. The arguments are as follows:

x

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

lags

specifies integer lags. The lags argument can be an integer matrix with $d$ elements. If so, the DIF function returns an $n\times d$ matrix where the $i$th column represents the difference between the time series and the lagged data for the $i$th lag. 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 DIF function is related to the LAG function.

For example, the following statements compute the difference between the time series and the lagged data:

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

Figure 23.91: Differences between Data and Lagged Data

dif
0 . .
0 2 .
0 1 .
0 3 6
0 2 6