Performing the Crosslist Selection Function |
There are two methods for performing the crosslist selection function. The first method uses two Fame namelists, and the second method uses one namelist and one BY group specified in the WHERE= clause of the INSET= option.
For example, suppose that your Fame database has a string case series named TICKER, so that when the Fame NL function is used on TICKER, it returns the namelist
Ticker = {AOL, C, CVX, F, GM, HPQ, IBM, INDUA, INTC, SPX, SUNW, XOM}
and your time series are named in fame_namelist2 as
{adjust, close, high, low, open, volume, uclose, uhigh, ulow, uopen, uvolume}
When you specify the following statements, then the 132 variables shown in Table 40.5 are selected by the CROSSLIST= option.
LIBNAME test sasefame 'physical name of test database' RANGE='01jan1999'd - '31mar1999'd CROSSLIST=(nl(ticker), {adjust, close, high, low, open, volume, uclose, uhigh, ulow, uopen, uvolume}) ;
AOL.ADJUST |
C.ADJUST |
CVX.ADJUST |
F.ADJUST |
AOL.CLOSE |
C.CLOSE |
CVX.CLOSE |
F.CLOSE |
AOL.HIGH |
C.HIGH |
CVX.HIGH |
F.HIGH |
AOL.LOW |
C.LOW |
CVX.LOW |
F.LOW |
AOL.OPEN |
C.OPEN |
CVX.OPEN |
F.OPEN |
AOL.UCLOSE |
C.UCLOSE |
CVX.UCLOSE |
F.UCLOSE |
AOL.UHIGH |
C.UHIGH |
CVX.UHIGH |
F.UHIGH |
AOL.ULOW |
C.ULOW |
CVX.ULOW |
F.ULOW |
AOL.UOPEN |
C.UOPEN |
CVX.UOPEN |
F.UOPEN |
AOL.UVOLUME |
C.UVOLUME |
CVX.UVOLUME |
F.UVOLUME |
AOL.VOLUME |
C.VOLUME |
CVX.VOLUME |
F.VOLUME |
GM.ADJUST |
HPQ.ADJUST |
IBM.ADJUST |
INDUA.ADJUST |
GM.CLOSE |
HPQ.CLOSE |
IBM.CLOSE |
INDUA.CLOSE |
GM.HIGH |
HPQ.HIGH |
IBM.HIGH |
INDUA.HIGH |
GM.LOW |
HPQ.LOW |
IBM.LOW |
INDUA.LOW |
GM.OPEN |
HPQ.OPEN |
IBM.OPEN |
INDUA.OPEN |
GM.UCLOSE |
HPQ.UCLOSE |
IBM.UCLOSE |
INDUA.UCLOSE |
GM.UHIGH |
HPQ.UHIGH |
IBM.UHIGH |
INDUA.UHIGH |
GM.ULOW |
HPQ.ULOW |
IBM.ULOW |
INDUA.ULOW |
GM.UOPEN |
HPQ.UOPEN |
IBM.UOPEN |
INDUA.UOPEN |
GM.UVOLUME |
HPQ.UVOLUME |
IBM.UVOLUME |
INDUA.UVOLUME |
GM.VOLUME |
HPQ.VOLUME |
IBM.VOLUME |
INDUA.VOLUME |
INTC.ADJUST |
SPX.ADJUST |
SUNW.ADJUST |
XOM.ADJUST |
INTC.CLOSE |
SPX.CLOSE |
SUNW.CLOSE |
XOM.CLOSE |
INTC.HIGH |
SPX.HIGH |
SUNW.HIGH |
XOM.HIGH |
INTC.LOW |
SPX.LOW |
SUNW.LOW |
XOM.LOW |
INTC.OPEN |
SPX.OPEN |
SUNW.OPEN |
XOM.OPEN |
INTC.UCLOSE |
SPX.UCLOSE |
SUNW.UCLOSE |
XOM.UCLOSE |
INTC.UHIGH |
SPX.UHIGH |
SUNW.UHIGH |
XOM.UHIGH |
INTC.ULOW |
SPX.ULOW |
SUNW.ULOW |
XOM.ULOW |
INTC.UOPEN |
SPX.UOPEN |
SUNW.UOPEN |
XOM.UOPEN |
INTC.UVOLUME |
SPX.UVOLUME |
SUNW.UVOLUME |
XOM.UVOLUME |
INTC.VOLUME |
SPX.VOLUME |
SUNW.VOLUME |
XOM.VOLUME |
Instead of using two namelists, you can use the WHERE= clause in an INSET= option to perform the crossproduct of the BY variables specified in your input data set via the WHERE= clause, with the members named in your namelist. The following statements define a SAS input data set named INSETA to use as input for the CROSSLIST= option instead of using the Fame namelist:
DATA INSETA; LENGTH tick $5; /* AOL, C, CVX, F, GM, HPQ, IBM, INDUA, INTC, SPX, SUNW, XOM */ tick='AOL'; output; tick='C'; output; tick='CVX'; output; tick='F'; output; tick='GM'; output; tick='HPQ'; output; tick='IBM'; output; tick='INDUA'; output; tick='INTC'; output; tick='SPX'; output; tick='SUNW'; output; tick='XOM'; output; RUN; LIBNAME test sasefame 'physical name of test database' RANGE='01jan1999'd - '31mar1999'd INSET=(inseta, where=tick) CROSSLIST=( {adjust, close, high, low, open, volume, uclose, uhigh, ulow, uopen, uvolume}) ;
Whether you use a SAS INSET statement with a WHERE clause or you use a Fame namelist in the CROSSLIST= statement, the two methods are equivalent ways of performing the same selection function. In the preceding example, the Fame ticker namelist corresponds to the SAS input data set’s BY variable named TICK.
Note that the WHERE=fame_bygroup must match the BY variable name used in your input data set in order for the CROSSLIST= option to perform the desired selection. If one of the time series listed in fame_namelist2 does not exist, the SASEFAME engine stops processing the remainder of the namelist. For complete results, make sure that your fame_namelist2 is accurate and does not name unknown variables. The same holds true for fame_namelist1 and the BY variable values named in your input data set and used in your WHERE= clause.