SAS/Ets User's Guide 51. 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 | 492 F Chapter 9 The COMPUTAB Procedure The BY variables contain values for the current BY group. For observations in the output data set from consolidation tables the consolidated BY variables have missing values. The special variable _TYPE_ is a numeric variable that can have one of three values 1 2 or 3. _TYPE_ 1 indicates observations from the normal report table produced for each BY group _TYPE_ 2 indicates observations from the _TOTAL_ consolidation table _TYPE_ 3 indicates observations from other consolidation tables. _TYPE_ 2 and _TYPE_ 3 observations have one or more BY variables with missing values. The special variable _NAME_ is a character variable of length 8 that contains the row or column name associated with the observation from the report table. If the input data set is transposed _NAME_ contains column names otherwise _NAME_ contains row names. If the input data set is transposed the remaining variables in the output data set are row variables from the report table. They are column variables if the input data set is not transposed. Examples COMPUTAB Procedure Example Using Programming Statements This example illustrates two ways of operating on the same input variables and producing the same tabular report. To simplify the example no report enhancements are shown. The manager of a hotel chain wants a report that shows the number of bookings at its hotels in each of four cities the total number of bookings in the current quarter and the percentage of the total coming from each location for each quarter of the year. Input observations contain the following variables REPTDATE report date LA number of bookings in Los Angeles ATL number of bookings in Atlanta CH number of bookings in Chicago and NY number of bookings in New York . The following DATA step creates the SAS data set BOOKINGS data bookings input reptdate date9. la atl ch ny datalines 01JAN1989 100 110 120 130 01FEB1989 140 150 160 170 01MAR1989 180 190 200 210 01APR1989 220 230 240 250 .
