Use Aggregate function to calculate a DIFFERENCE.

I am trying to calculate a Forecast Variance "VR" from my Cube.  I have Daily Transaction and Forecast [Rec Type] (Record Types) coded "GL" (General Ledger or Sales), "FC" (Forecast) for all Products.  I created a
new MEMBER "VR" (Variance) as shown below.  This produces the SUM(Aggregate) of "GL" and "FC".  What I need is the DIFFERENCE.  I tried placing a (-1) in my formula.  It passed the syntax check but does not
produce any "VR" results.  Any suggestions would be appreciated.  Here is my Script View:
Thanks!
CALCULATE;                   
CREATE MEMBER CURRENTCUBE.[Measures].[SalesMTD]
 AS SUM(MTD([Dates].[Year -  Quarter -  Month -  Date].CurrentMember), [Measures].[Prime Qty]),
FORMAT_STRING = "#,##0;-#,##0",
NON_EMPTY_BEHAVIOR = { [Prime Qty] },
VISIBLE = 1 ,  ASSOCIATED_MEASURE_GROUP = 'PSI Activity';   
CREATE MEMBER CURRENTCUBE.[PSI Activity].[Rec Type].[All].[VR]
 AS Aggregate(
   ([PSI Activity].[Rec Type].[FC]),
   ([PSI Activity].[Rec Type].[GL])
  }, [Measures].CurrentMember
FORMAT_STRING = "#,##0;-#,##0",
NON_EMPTY_BEHAVIOR = { [Prime Qty] },
VISIBLE = 1 ,  ASSOCIATED_MEASURE_GROUP = 'PSI Activity'  ;
Mario

TRy the below query.Wont it give the expected result?
CREATE MEMBER CURRENTCUBE.[PSI Activity].[Rec Type].[All].[VR]
 AS (
   ([PSI Activity].[Rec Type].[FC],[Measures].CurrentMember)-
   ([PSI Activity].[Rec Type].[GL],[Measures].CurrentMember)
FORMAT_STRING = "#,##0;-#,##0", 
NON_EMPTY_BEHAVIOR = { [Prime Qty] }, 
VISIBLE = 1 ,  ASSOCIATED_MEASURE_GROUP = 'PSI Activity'  ;

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    Edited by: BluShadow on 16-May-2011 09:39
    added {noformat}{noformat} tags.  Please read: {message:id=9360002} for details on how to post 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                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            

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Here is the details.
In the infoprovider the data is like this:
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Thanks,
Terrence

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    JOB300 - started at 12PM - stopped at 2PM
    The query would tell me that JOB1 ran with a concurrency of 2 because JOB1 and JOB2
    were running started and finished within the same time. JOB2 ran with the concurrency
    of 3 because all jobs ran within its start and stop time. The output would look like this.
    JOB START STOP CONCURRENCY
    === ==== ==== =========
    100 9AM 11AM 2
    200 10AM 3PM 3
    300 12PM 2PM 2
    I've been looking at this post, and this one if very similar...
    Analytic functions using window date range
    Here is the sample data..
    CREATE TABLE TEST_JOB
    ( jobid NUMBER,
    created_time DATE,
    start_time DATE,
    stop_time DATE
    insert into TEST_JOB values (100, sysdate -1, to_date('05/04/08 09:00:00','MM/DD/YY hh24:mi:ss'), to_date('05/04/08 11:00:00','MM/DD/YY hh24:mi:ss'));
    insert into TEST_JOB values (200, sysdate -1, to_date('05/04/08 10:00:00','MM/DD/YY hh24:mi:ss'), to_date('05/04/08 13:00:00','MM/DD/YY hh24:mi:ss'));
    insert into TEST_JOB values (300, sysdate -1, to_date('05/04/08 12:00:00','MM/DD/YY hh24:mi:ss'), to_date('05/04/08 14:00:00','MM/DD/YY hh24:mi:ss'));
    select * from test_job;
    JOBID|CREATED_TIME |START_TIME |STOP_TIME
    ----------|--------------|--------------|--------------
    100|05/04/08 09:28|05/04/08 09:00|05/04/08 11:00
    200|05/04/08 09:28|05/04/08 10:00|05/04/08 13:00
    300|05/04/08 09:28|05/04/08 12:00|05/04/08 14:00
    Any help with this query would be greatly appreciated.
    thanks.
    -peter

    after some checking the model rule wasn't working exactly as expected.
    I believe it's working right now. I'm posting a self-contained example for completeness sake.I use 2 functions to convert back and forth between epoch unix timestamps, so
    I'll post them here as well.
    Like I said I think this works okay, but any feedback is always appreciated.
    -peter
    CREATE OR REPLACE FUNCTION date_to_epoch(p_dateval IN DATE)
    RETURN NUMBER
    AS
    BEGIN
    return (p_dateval - to_date('01/01/1970','MM/DD/YYYY')) * (24 * 3600);
    END;
    CREATE OR REPLACE FUNCTION epoch_to_date (p_epochval IN NUMBER DEFAULT 0)
    RETURN DATE
    AS
    BEGIN
    return to_date('01/01/1970','MM/DD/YYYY') + (( p_epochval) / (24 * 3600));
    END;
    DROP TABLE TEST_MODEL3 purge;
    CREATE TABLE TEST_MODEL3
    ( jobid NUMBER,
    start_time NUMBER,
    end_time NUMBER);
    insert into TEST_MODEL3
    VALUES (300,date_to_epoch(to_date('05/07/2008 10:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 19:00','MM/DD/YYYY hh24:mi')));
    insert into TEST_MODEL3
    VALUES (200,date_to_epoch(to_date('05/07/2008 09:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 12:00','MM/DD/YYYY hh24:mi')));
    insert into TEST_MODEL3
    VALUES (400,date_to_epoch(to_date('05/07/2008 10:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 14:00','MM/DD/YYYY hh24:mi')));
    insert into TEST_MODEL3
    VALUES (500,date_to_epoch(to_date('05/07/2008 11:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 16:00','MM/DD/YYYY hh24:mi')));
    insert into TEST_MODEL3
    VALUES (600,date_to_epoch(to_date('05/07/2008 15:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 22:00','MM/DD/YYYY hh24:mi')));
    insert into TEST_MODEL3
    VALUES (100,date_to_epoch(to_date('05/07/2008 09:00','MM/DD/YYYY hh24:mi')),
    date_to_epoch(to_date('05/07/2008 23:00','MM/DD/YYYY hh24:mi')));
    commit;
    SELECT jobid,
    epoch_to_date(start_time)start_time,
    epoch_to_date(end_time)end_time,
    n concurrency
    FROM TEST_MODEL3
    MODEL
    DIMENSION BY (start_time,end_time)
    MEASURES (jobid,0 n)
    (n[any,any]=
    count(*)[start_time<= cv(start_time),end_time>=cv(start_time)]+
    count(*)[start_time > cv(start_time) and start_time <= cv(end_time), end_time >= cv(start_time)]
    ORDER BY start_time;
    The results look like this:
    JOBID|START_TIME|END_TIME |CONCURRENCY
    ----------|---------------|--------------|-------------------
    100|05/07/08 09:00|05/07/08 23:00| 6
    200|05/07/08 09:00|05/07/08 12:00| 5
    300|05/07/08 10:00|05/07/08 19:00| 6
    400|05/07/08 10:00|05/07/08 14:00| 5
    500|05/07/08 11:00|05/07/08 16:00| 6
    600|05/07/08 15:00|05/07/08 22:00| 4

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