TAILIEUCHUNG - SAS/ETS 9.22 User's Guide 163

SAS/Ets User's Guide 163. 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 | 1612 F Chapter 23 The SIMILARITY Procedure If the ACCUMULATE TOTAL option is specified the data are accumulated as follows O1MAR1999 40 O1APR1999 . O1MAY1999 90 If the ACCUMULATE AVERAGE option is specified the data are accumulated as follows O1MAR1999 20 O1APR1999 . O1MAY1999 30 If the ACCUMULATE MINIMUM option is specified the data are accumulated as follows O1MAR1999 10 O1APR1999 . O1MAY1999 20 If the ACCUMULATE MEDIAN option is specified the data are accumulated as follows O1MAR1999 20 01APR1999 . O1MAY1999 20 If the ACCUMULATE MAXIMUM option is specified the data are accumulated as follows O1MAR1999 30 O1APR1999 . O1MAY1999 50 If the ACCUMULATE FIRST option is specified the data are accumulated as follows O1MAR1999 10 O1APR1999 . O1MAY1999 50 If the ACCUMULATE LAST option is specified the data are accumulated as follows O1MAR1999 30 O1APR1999 . O1MAY1999 20 If the ACCUMULATE STDDEV option is specified the data are accumulated as follows Missing Value Interpretation F 1613 O1MAR1999 O1APR1999 . O1MAY1999 As can be seen from the preceding examples even though the data set observations contain no missing values the accumulated time series can have missing values. Missing Value Interpretation Sometimes missing values should be interpreted as unknown values. But sometimes missing values are known such as when missing values are created from accumulation and no observations should be interpreted as no zero value. In the former case the SETMISSING option in the ID INPUT or TARGET statement can be used to interpret how missing values are treated. The SETMISSING 0 option should be used when missing observations are to be treated as no zero values. In other cases missing values should be interpreted as global values such as minimum or maximum values of the accumulated series. The accumulated and interpreted time series is used in subsequent analyses. The SETMISSING 0 option should be used with missing observations are to be treated as a zero value. In other

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