And what do you want as a result in such cases? ... View more

I think what you want is   count (distinct whichc(anrind, 'High', 'Low')) as hlcnt ... View more

Here is an example using proc expand with 5 lags   data have(drop=i); call streaminit(86589); do i = 1 to 25; x = rand("uniform"); output; end; run; proc expand data=have out=want(drop=TIME); convert x=x_sum5 / transformout = (movsum 5 trimleft 4); convert x=x_rev5 / transformout = (reverse movsum 5 reverse trimright 4); run; proc expand is part of SAS/ETS, SAS econometrics and time series procedures. ... View more

These are log-likelihood type 1 analyses, describing the log-likelihood improvement as each parameter is added to the model. The Chi-square p-values describe the improvements as significant or not. So, when parameter a is lastly introduced in the model fit, the improvement is evaluated after the other parameters are taken into account. The tables above would indicate that the inclusion of parameter a does not improve significantly the model fit. ... View more

According to the documentation of the COUNTREG procedure, the parameters of the ZIP model are estimated by maximum likelihood. The log-likelihood functions are given here. ... View more

Should be done in a single step:   proc sql; create table Banded as select case when score_band="le550" then "le560" else score_band end as score_band_new, count(*) as Volume, sum(Projected12) as Projected from ac_banded group by calculated score_band_new; quit; (untested) ... View more

I am not a fedSQL user but for such a simple condition, you could use   select * from PUBLIC.JS_MTOS_V2AA where codopera not in (select codopera from MKT.OUTYS) No? ... View more

I had to make a few assumptions about your questions, but this would be my best guess answer:   /* generate dummy data t, y(t) */ data have; call streaminit(76876); do _n_ = 1 to 200; t + 1; y + rand("NORMAL"); output; end; stop; run; /* Arrange the data into windows */ data sets; set have; do set = _n_ - 99 to _n_; if 1 <= set <= 100 then output; end; run; proc sort data = sets; by set t; run; /* Calculate autoregression estimates */ proc autoreg data=sets outest=est plots=none noprint; by set; model y = / nlag=1; output out=preds residual=res; run; /* Compute statistics on original data and residuals for each data window */ proc univariate data=preds noprint; by set; var y res; output out=setstats var=yvar resvar skewness=yskew resskew; run; ... View more

If h1_unmet takes two values, the statement Class h1_unmet; defines two samples. The option sides=2 requests a two-sided test, i.e. the cg_age difference will be significant if it falls on the extreme left tail or the extreme right tail of the T distribution. ... View more

Please check the Log after you run your code. This should show you that dataset cleanp_n has the same number of obs as stcp.cleanedp2. ... View more

I guess proc surveyselect was used with option OUTALL and split according to the newly created variable Selected. Example:   1 OPTIONS NONOTES NOSTIMER NOSOURCE NOSYNTAXCHECK; 68 69 proc surveyselect data=sashelp.class out=classSamples outall sampsize=15 seed=75868; 70 run; NOTE: The data set WORK.CLASSSAMPLES has 19 observations and 6 variables. NOTE: PROCEDURE SURVEYSELECT a utilisé (Durée totale du traitement) : real time 0.02 seconds cpu time 0.03 seconds 71 72 data mb xv; 73 set classSamples; 74 if Selected then output mb; 75 else output xv; 76 run; NOTE: There were 19 observations read from the data set WORK.CLASSSAMPLES. NOTE: The data set WORK.MB has 15 observations and 6 variables. NOTE: The data set WORK.XV has 4 observations and 6 variables. NOTE: DATA statement a utilisé (Durée totale du traitement) : real time 0.00 seconds cpu time 0.01 seconds ... View more

You can use the FEEDBACK option:   proc SQL feedback; Select a.apple, a.lemon, b.size, b.colour, weight, origin from fruit a left join info b on a.cost=b.cost; quit;   it will expand the query in full details. ... View more

Yes, to get the cross product of two tables,   select * from A, B; /* is equivalent to */ select * from A cross join B; ... View more

This is standard alternative SQL syntax for simple joins. It is equivalent to:   proc sql; create table mthbal_bal as select mthbal_org as ambs_org, mthbal_acct as ambs_acct, mthbal_curr_bal as mthend_bal, mthbal_crlim, intnx("month", a.mthbal_load_Dt,0,"E") as mthend_date from mthbal a inner join acct_new_all b on a.mthbal_org=b.org_cod and a.mthbal_acct=b.account_no; quit; ... View more