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SAS/Ets 9.22 User's Guide 12. Provides detailed reference material for using SAS/ETS software and guides you through the analysis and forecasting of features such as univariate and multivariate time series, cross-sectional time series, seasonal adjustments, multiequational nonlinear models, discrete choice models, limited dependent variable models, portfolio analysis, and generation of financial reports, with introductory and advanced examples for each procedure. You can also find complete information about two easy-to-use point-and-click applications: the Time Series Forecasting System, for automatic and interactive time series modeling and forecasting, and the Investment Analysis System, for time-value of money analysis of a variety of investments | 102 F Chapter 3 Working with Time Series Data data uscpi set uscpi d0 intnx month date 0 - 1 d1 intnx month date 1 - 1 nSunday intck week.1 d0 dl nMonday intck week.2 d0 d1 nTuesday intck week.3 d0 d1 nWedday intck week.4 d0 d1 nThurday intck week.5 d0 d1 nFriday intck week.6 d0 d1 nSatday intck week.7 d0 d1 drop d0 dl run Since the INTCK function counts the number of interval beginning dates between two dates the number of Sundays is computed by counting the number of week boundaries between the last day of the previous month and the last day of the current month. To count Mondays Tuesdays and so forth shifted week intervals are used. The interval type WEEK.2 specifies weekly intervals starting on Mondays WEEK.3 specifies weeks starting on Tuesdays and so forth. Checking Data Periodicity Suppose you have a time series data set and you want to verify that the data periodicity is correct the observations are dated correctly and the data set is sorted by date. You can use the INTCK function to compare the date of the current observation with the date of the previous observation and verify that the dates fall into consecutive time intervals. For example the following statements verify that the data set USCPI is a correctly dated monthly data set. The RETAIN statement is used to hold the date of the previous observation and the automatic variable _N_ is used to start the verification process with the second observation. data _null_ set uscpi retain prevdate if _n_ 1 then if intck month prevdate date A 1 then put Bad date sequence at observation number _n_ prevdate date run Filling In Omitted Observations in a Time Series Data Set Most SAS ETS procedures expect input data to be in the standard form with no omitted observations in the sequence of time periods. When data are missing for a time period the data set should contain a missing observation in which all variables except the ID variables have missing values. Using Interval Functions for Calendar Calculations F 103
