oracle10g - Oracle cumulative totals by week for a given date range -

i using following query column totals week given date range...

select to_char(week_start - 1, 'dd-mon-yy') week_end, run_qty, acc_qty, case when run_qty <> 0 round(acc_qty/run_qty, 4) else 0 end pct    (select week_start, sum(run_qty) run_qty, sum(acc_qty) acc_qty            (select trunc(next_day(trunc(created_date), 'monday')) week_start, nvl(sum(run_qty), 0) run_qty, nvl(sum(accepted_qty), 0) acc_qty                    shema.table_a                    (some conditions)                     , created_date between :fromdate , :todate                    group trunc(next_day(trunc(created_date), 'monday'))                  union                  select trunc(next_day(trunc(to_date(zday, 'dd-mon-rrrr')), 'monday')) week_start, 0run_qty, 0acc_qty                    (select :fromdate + (level - 1) zday                            dual                          connect level <= (:todate - :fromdate)))           group week_start           order week_start desc) 

with input paramters of :fromdate = 4/31/2015 , :todate = 6/25/2015, gives me last day of each week (week defined monday - sunday), run total each each week, accepted total each week, , pct of run total accepted each week, in result set looks so...

28-jun-2015 0 0 0

21-jun-2015 100 50 0.5

14-jun-2015 50 40 0.8

07-jun-2015 0 0 0

31-may-2015 0 0 0

24-may-2015 50 40 0.75

17-may-2015 80 50 0.625

10-may-2015 60 20 0.3333

03-may-2015 0 0 0

can use similar approach in order calculate running total of run , accepted quantities , percentage of quantity accepted on date range provided? (to give me result set like)...

28-jun-2015 340 200 0.5882

21-jun-2015 340 200 0.5882

14-jun-2015 240 150 0.625

07-jun-2015 190 110 0.5789

31-may-2015 190 110 0.5789

24-may-2015 190 110 0.5789

17-may-2015 140 70 0.5

10-may-2015 60 20 0.3333

03-may-2015 0 0 0

i figured out... in case runs thread searching solution similar issue, wrapped query above inside...
select week_end, run_qty, acc_qty, pct

from (query above)
model dimension by(row_number() on (order to_date(week_end, 'dd-mon-yy') asc) rec)

measures(week_end, run_qty, acc_qty, pct)

rules(

run_qty[rec > 1] order rec = run_qty[cv()] + run_qty[cv() - 1],

acc_qty[rec > 1] order rec = acc_qty[cv()] + acc_qty[cv() - 1],

pct[rec >= 0] order rec = case when run_qty[cv()] <> 0 round(acc_qty[cv()]/run_qty[cv()], 4) else 0 end )

order to_date(week_end, 'dd-mon-yy') desc
...and runs quickly, giving me expected results