Beginner at simulation and want to get my feet wet

[iiibbb]

I am new to simulation and would like to do what I hope is a simple case.

I have a dataset with an N of 85.  The data consists of the weights of truckloads of material that were weighed with scales, and data that estimates the weight based on machine performance.  The estimate by truckload is interesting and can be off for an individual load by a good margin enough, but what most end users will care about is its accuracy over the course of an entire field... 80 truckloads.  So it's the sum of the predictions that matters to me.

So I want to run a simulation where I randomly draw 5%, 10%, 15%, 20% etc of the loads, run a regression on those, apply it to the entire population, and see where the variability in the error between cummulative predicted mass, and the cummulative weighed mass becomes acceptable from a practical standpoint.

Is this something I can execute with do loops?  Or would it be possible to do it with proc surveyselect and a do loop?

Perhaps there are some good online examples or primers out there?

[iiibbb]

I am new to simulation and would like to do what I hope is a simple case.

I have a dataset with an N of 85.  The data consists of the weights of truckloads of material that were weighed with scales, and data that estimates the weight based on machine performance.  The estimate by truckload is interesting and can be off for an individual load by a good margin enough, but what most end users will care about is its accuracy over the course of an entire field... 80 truckloads.  So it's the sum of the predictions that matters to me.

So I want to run a simulation where I randomly draw 5%, 10%, 15%, 20% etc of the loads, run a regression on those, apply it to the entire population, and see where the variability in the error between cummulative predicted mass, and the cummulative weighed mass becomes acceptable from a practical standpoint.

Is this something I can execute with do loops?  Or would it be possible to do it with proc surveyselect and a do loop?

Perhaps there are some good online examples or primers out there?

[PGStats]

Please provide an example dataset.

[iiibbb]

Here is the data

day, load, the "true" weight of the load, and the machine's guess.

I want to simulate draws from this population, to make a regression and output the slope and intercept, and use those betas to estimate the mass of the sum total of the entire population.  Getting the "true" weight is inconvenient, but until we can perfect the way this machine guesses the weight I'd like to figure out what reasonble rate of subsampling it would take to still get a decent estimate of the sum total.

Thanks, I'm eager to learn something about looping and macros.

day	load	weighed	estimated
1	101	4115	4787
1	102	8265	7828
1	103	7534	4085
1	104	10205	3898
1	105	10466	5312
1	106	11719	5546
1	107	4489	4751
2	201	7526	8356
2	205	9379	6531
2	207	7212	5247
2	208	6690	8670
2	209	3776	4710
2	210	11493	12668
2	211	2097	1360
2	212	6281	8667
2	213	8456	7896
2	214	7926	6321
2	215	4637	5511
3	301	7534	8933
3	302	10666	6754
3	303	6177	4246
3	304	8456	4855
3	305	8004	5491
3	306	8056	6590
3	307	8674	6923
3	308	7195	4783
3	309	3489	2589
5	501	3950	4397
5	502	8665	9732
5	503	7238	7979
5	504	8587	8999
5	505	7882	5760
5	506	4994	5035
5	507	4454	3463
5	508	5594	5235
5	509	8891	9772
5	510	5229	5880
5	511	6786	5622
5	512	7343	7967
5	513	8291	9275
6	604	11963	9988
6	606	4367	895
6	607	5577	5184
6	608	12371	11786
6	610	6673	7947
6	611	5820	4279
6	612	6055	8555
6	613	5881	4360
6	614	4663	2393
6	615	4228	4685
6	616	4759	898
6	617	3854	4739
6	618	8709	9386
6	619	8691	9333
6	620	8126	9509
6	621	8138	9356
6	622	11536	10899
7	701	3619	4401
7	702	3271	3450
7	703	6725	7975
7	704	7265	8109
7	705	5629	5590
7	706	5394	5497
7	707	18340	17964
7	708	1775	1459
7	709	5037	5525
7	710	15730	11124
7	711	6542	7216
7	712	6951	7129
7	713	8108	7028
7	714	2984	3470
7	715	1366	1791
8	801	4176	5212
8	802	6212	6630
8	803	5342	6759
8	804	5203	5465
8	805	6308	5641
8	806	6647	5463
8	807	5777	4818
8	808	6795	3058
8	809	2906	1745
8	810	6769	4742
8	811	5890	5015
8	812	6656	5581
8	813	3906	3276

[iiibbb]

I suspect survey select and a loop are what I need... perhaps as a macro.

I've done little with loops in the past so I don't know if/how to imbed a procedure.  The syntax seems a little quirky.

[PGStats]

Looping is not really needed for this type of investigation. You can manage with BY processing. Here is what you could do, assuming your data is in dataset have:

/* Define simulation for a single sample rate */
%macro simul(pct);
/* Generate random samples */
proc surveyselect data=have samprate=&pct. rep=100 out=sample&pct.;
run;

/* Perform a regression on each sample to predict true weight */
proc reg data=sample&pct. outest=est&pct. plots=none noprint;
by replicate;
predict: model weighed = estimated;
run;

/* Predict true weight on the whole dataset */
proc score score=est&pct. data=have out=score&pct. type=parms;
by replicate;
var estimated;
run;

/* Calculate total weights for each sample */
proc sql;
create table summ&pct. as
select
    &pct. as sampRate label="Sample Rate",
    replicate,
    sum(predict) as totalPredicted label="Predicted Total Weight"
from score&pct.
group by replicate;
delete from weights where samprate=&pct.;
quit;

/* Accumulate results in weights dataset */
proc append base=weights data=summ&pct.; run;
%mend simul;

/* Call macro for each sample rate */
%simul(5);
%simul(10);
%simul(15);
%simul(20);
%simul(25);
%simul(30);

/* Calculate the true total weight */
proc sql noprint;
select sum(weighed) into :trueTotalWeight
from have;
quit;

/* Look at the distributions of total weight estimates, 
 robust measures of dispersion in particular */ 
proc univariate data=weights location=&trueTotalWeight. robustscale;
by samprate;
var totalPredicted;
run;

[iiibbb]

Wow, a lot more than I was hoping.  Thank you!!

[SAS_inquisitive]

@PGStats I have been using Proc SQL a lot (mostly statements- "So Few Workers Go Home Ontime". I know we can use execute statment  to manipulate external RDBM. But this stament is complete new to me in your above program.  Can we use Data step stament in Proc SQL other than Data set options?  Thanks !

delete from weights where samprate=&pct.;

[PGStats]

There is more to standard SQL than select statements. Check out delete, insert and update statements.

SAS additions are dateset options, as you mentioned, macro variable creation (select ... into :macrovar), and SAS functions (including powerful date, text distance, text matching, and user defined FCMP functions).