how to calculate a rolling average

[brenda023]

Hi

I'm hoping someone can help me solve this.  I've been looking up proc expand as a possible solution, but haven't had any luck.

I'm trying to create a moving average, but my data has some gaps and I want the moving average to reset each time I get to a new ID.  Each ID should have 10 weeks of data, but sometimes, the information isn't complete (e.g missing weeks of data)... so my data set looks something like this:

ID	Week	Count
D1	1	13
D1	2	11
D1	3	9
D1	4	8
D1	5	10
D1	6	9
D1	7	5
D1	8	7
C1	2	1
C1	4	4
C1	5	5
C1	7	2
C1	8	3
C1	9	5
C1	10	2
E1	3	7
E1	5	9
E1	6	7
E1	8	5
E1	9	7

The resulting data set I'm trying to get is this.  Where all IDs have 10 weeks, and when there is a week missing, the Count value is set to zero, and the average is based on the the 4 previous values (e.g. average for week 4 for ID D1 is (13+11+9+8)/4 .  But once I get to a new ID, I'd like the average to re-set.

ID	Week	Count	Average
D1	1	13	.
D1	2	11	.
D1	3	9	.
D1	4	8	10
D1	5	10	10
D1	6	9	9
D1	7	5	8
D1	8	7	8
D1	9	0	5
D1	10	0	3
C1	1	0	2
C1	2	1	.
C1	3	0	.
C1	4	4	.
C1	5	5	3
C1	6	0	2
C1	7	2	3
C1	8	3	3
C1	9	5	3
C1	10	2	3
E1	1	0	.
E1	2	0	.
E1	3	7	.
E1	4	0	2
E1	5	9	4
E1	6	7	6
E1	7	0	4
E1	8	5	5
E1	9	7	5
E1	10	0	3

Thanks in advance

[Reeza]

First you'll need to create a time series with no missing values and then you can use either a data step with the lag function if it's only four time periods or you could use proc expand. Both methods are illustrated below:

data have;

input ID $ Week Count;

cards;

D1 1 13

D1 2 11

D1 3 9

D1 4 8

D1 5 10

D1 6 9

D1 7 5

D1 8 7

C1 2 1

C1 4 4

C1 5 5

C1 7 2

C1 8 3

C1 9 5

C1 10 2

E1 3 7

E1 5 9

E1 6 7

E1 8 5

E1 9 7

;

run;

data weeks;

do week=1 to 10;

output;

end;

run;

proc sql;

create table step1 as

select t1.id, t1.week, coalesce(t2.count, 0) as count

from (

select distinct a.id, b.week

from have as a

cross join weeks as b) as t1

left join have as t2

on t1.id=t2.id

and t1.week=t2.week

order by t1.id, t1.week;

quit;

data want1;

  set step1;

  by id;

  if first.id then n_count=1;

  else n_count+1;

  lag1=lag1(count);

  lag2=lag2(count);

  lag3=lag3(count);

  if n_count>=4 then rolling_avg=(count+lag1+lag2+lag3)/4;

  else rolling_avg=.;

  drop lag:;

run;

proc expand data=step1 out=want2;

by id;

id week;

convert count=rolling_avg4 / transformout=(movave 4 trimleft 3);

run;

[stat_sas]

data base;

do id = 'D1','C1','E1';

do week=1 to 10;

output;

end;

end;

run;

proc sql;

create table want as

select b.id,b.week,coalesce(a.count,0) as count

from base b left join have a

on b.id=a.id

and b.week=a.week;

quit;

data final;

set want;

by id;

four_week_moving_avg=(count+lag(count)+lag2(count)+lag3(count))/4;

format four_week_moving_avg 3.0;

if week < 4 then four_week_moving_avg=.;

run;

proc print data=final;

run;

[Ksharp]

data have;
input ID $ Week Count;
cards;
D1 1 13
D1 2 11
D1 3 9
D1 4 8
D1 5 10
D1 6 9
D1 7 5
D1 8 7
C1 2 1
C1 4 4
C1 5 5
C1 7 2
C1 8 3
C1 9 5
C1 10 2
E1 3 7
E1 5 9
E1 6 7
E1 8 5
E1 9 7
;
run;

proc sql;
create table want as
select x.*,case when week lt 4 then .
              else (select sum(count)/4 from have where id=x.id and week between x.week-3 and x.week)
           end as average
from (
     select t1.id, t1.week, coalesce(t2.count, 0) as count
      from ( select * from (select distinct id from have),(select distinct week from have) ) as t1
       left join have as t2 on t1.id=t2.id and t1.week=t2.week 
     ) as x;
quit;

Xia Keshan