You are here: Symbol Reference > StatTimeSerAnalysis Namespace > Functions > StatTimeSerAnalysis.ARARForecast Function
Stats Master VCL
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Example

Fit and then forecast time series values by using ARAR algorithm. Before applying the ARAR algorithm, use the shortening filter on original series.

Uses MtxExpr, StatTimeSerAnalysis, Math387;
procedure Example;
var timeseries,s,filter,phi: Vector;
  forecasts,stderrs: Vector;
  l1,l2,l3,tau: Integer;
  s2,rmse: double;
 begin
   timeseries.LoadFromFile('deaths.vec');
   // #1: shorten series
   ShortenFilter(timeSeries,s,tau,Filter);
   // #2 : fit ARAR model on shortened series
   ARARFit(s,Phi,l1,l2,l3,s2,13);
   // #3: forecast 100 values by using ARAR fit parameters
   ARARForecast(timeseries,Phi,Filter,tau,l1,l2,l3,s.mean,100,forecasts,stderrs,rmse);
end;
#include "MtxExpr.hpp"
#include "StatTimeSerAnalysis.hpp"
void __fastcall Example();
{
    sVector timeseries,s,filter,phi,forecasts,stderrs;
    int l1,l2,l3,tau;
    double s2, rmse;
    timeseries.LoadFromFile("deaths.vec");
    // #1: shorten series
    ShortenFilter(timeseries,s,tau,filter);
    // #2 : fit ARAR model on shortened series
    ARARFit(s,phi,l1,l2,l3,s2,13);
    // #3: forecast 100 values by using ARAR fit parameters
    ARARForecast(timeseries,phi,filter,tau,l1,l2,l3,s->Mean(),100,forecasts,stderrs,rmse);
}
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