The EXPAND Procedure |

Interpolating Missing Values |

To interpolate missing values in time series without converting the observation frequency, leave off the TO= option on the PROC EXPAND statement. For example, the following statements interpolate any missing values in the time series in the data set ANNUAL.

proc expand data=annual out=new from=year; id date; convert x y z; convert a b c / observed=total; run;

This example assumes that the variables X, Y, and Z represent point-in-time values observed at the beginning of each year. (The default value of the OBSERVED= option is OBSERVED=BEGINNING.) The variables A, B, and C are assumed to represent annual totals.

To interpolate missing values in variables observed at specific points in time, omit both the FROM= and TO= options and use the ID statement to supply time values for the observations. The observations do not need to be periodic or form regular time series, but the data set must be sorted by the ID variable. For example, the following statements interpolate any missing values in the numeric variables in the data set A.

proc expand data=a out=b; id date; run;

If the observations are equally spaced in time, and all the series are observed as beginning-of-period values, only the input and output data sets need to be specified. For example, the following statements interpolate any missing values in the numeric variables in the data set A using a cubic spline function, assuming that the observations are at equally spaced points in time.

proc expand data=a out=b; run;

Refer to the section Missing Values for further information.

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