HI, i'm using Visual Forecasting. While using atsm package in TSMODEL procedure, I wonder the difference  diagnose.setOption('holdout', 6); and forecast.setOption('holdout',6).   **i'm using Auto-forecasting node.     proc tsmodel data = &vf_libIn.."&vf_inData"n %if "&vf_inEventObj" ne "" %then %do; inobj = (&vf_inEventObj) %end; outobj = ( outfor = &vf_libOut.."&vf_outFor"n outstat = &vf_libOut.."&vf_outStat"n outmodelinfo = &vf_libOut.."&vf_outModelInfo"n ) outlog = &vf_libOut.."&vf_outLog"n ; *define time series ID variable and the time interval; id &vf_timeID interval = &vf_timeIDInterval; *define time series and the corresponding accumulation methods; %vf_varsTSMODEL; *define the by variables if exist; %if "&vf_byVars" ne "" %then %do; by &vf_byVars; %end; *using the ATSM (Automatic Time Series Model) package; require atsm; *starting user script; submit; *declaring the ATSM objects; /* TSDF: Time series data frame used to group series variables for DIAGNOSE and FORENG objects DIAGNOSE: Automatic time series model generation FORENG: Automatic time series model selection and forecasting DIAGSPEC: Diagnostic control options for DIAGNOSE object OUTFOR: Collector for FORENG forecasts OUTSTAT: Collector for FORENG forecast performance statistics */ declare object diagnose(diagnose); declare object diagspec(diagspec); declare object dataframe(tsdf); declare object forecast(foreng); declare object outfor(outfor); declare object outstat(outstat); declare object outmodelinfo(outmodelinfo); *initialize the tsdf object and assign the time series roles; rc = dataframe.initialize(); rc = dataframe.addY(&vf_depVar); *add independent variables to the tsdf object if there is any; %if "&vf_indepVars" ne "" %then %do; %vf_addXTSMODEL(dataframe); %end; %if "&vf_inEventObj" ne "" or "&vf_events" ne "" %then %do; declare object ev1(event); rc = ev1.Initialize(); %vf_addEvents(dataframe, ev1); %end; *open the diagspec object and enable ESM and ARIMAX model class for diagnose; rc = diagspec.open(); rc = diagspec.setESM(); rc = diagspec.setARIMAX(); rc = diagspec.setOption('criterion',"&_modelSelection_criteria"); rc = diagspec.close(); *set the diagnose object using the diagspec object and run the diagnose process; rc = diagnose.initialize(dataframe); rc = diagnose.setSpec(diagspec); /*holdout1 rc = diagnose.setOption('holdout', 6);*/ rc = diagnose.run(); *initialize the foreng object with the diagnose result and run model selecting and generate forecasts; rc = forecast.initialize(diagnose); rc = forecast.setOption('criterion',"&_modelSelection_criteria"); rc = forecast.setOption('lead',&vf_lead); rc = forecast.setOption('horizon',&vf_horizonStart); /*holdout2 rc = forecast.setOption('holdout',6);*/ rc = forecast.setOption('minobs.trend',2); rc = forecast.setOption('minobs.mean',2); %if "&vf_allowNegativeForecasts" eq "FALSE" %then %do; rc = forecast.setOption('fcst.bd.lower',0); %end; rc = forecast.run(); *collect the forecast and statistic-of-fit from the forgen object run results; rc = outfor.collect(forecast); rc = outstat.collect(forecast); rc = outmodelinfo.collect(forecast); endsubmit; quit; *generate outinformation CAS table; data &vf_libOut.."&vf_outInformation"n; set work.sforecast_outInformation; run; How to works these code on model?   What is the difference with the result of model A and model B?   model A : (add this code)  /*holdout1*/ rc = diagnose.setOption('holdout',6); model B : (add this code) /*holdout2*/ rc = forecast.setOption('holdout',6); <result> Thank u 🙂 <result>     ... View more