Detection of Level Changes in the Nile River Data

/*--------------------------------------------------------------

                    SAS Sample Library

        Name: ariex06.sas
 Description: Example program from SAS/ETS User's Guide,
              The ARIMA Procedure
       Title: Detection of Level Changes in the Nile River Data
     Product: SAS/ETS Software
        Keys: time series analysis
        PROC: ARIMA
       Notes:

--------------------------------------------------------------*/

data nile;
   input level @@;
   year = intnx( 'year', '1jan1871'd, _n_-1 );
   format year year4.;
datalines;
1120  1160  963  1210  1160  1160  813  1230   1370  1140
995   935   1110 994   1020  960   1180 799    958   1140
1100  1210  1150 1250  1260  1220  1030 1100   774   840
874   694   940  833   701   916   692  1020   1050  969
831   726   456  824   702   1120  1100 832    764   821
768   845   864  862   698   845   744  796    1040  759
781   865   845  944   984   897   822  1010   771   676
649   846   812  742   801   1040  860  874    848   890
744   749   838  1050  918   986   797  923    975   815
1020  906   901  1170  912   746   919  718    714   740
;

/*-- ARIMA(0, 1, 1) Model --*/
proc arima data=nile;
   identify var=level(1);
   estimate q=1 noint method=ml;
   outlier maxnum= 5 id=year;
run;

data nile;
   set nile;
   AO1877 = ( year = '1jan1877'd );
   AO1913 = ( year = '1jan1913'd );
   LS1899 = ( year >= '1jan1899'd );
run;

/*-- MA1 Model with Outliers --*/
proc arima data=nile;
   identify var=level
            crosscorr=( AO1877 AO1913 LS1899 );
   estimate q=1
            input=( AO1877 AO1913 LS1899 )
            method=ml;
   outlier maxnum=5 alpha=0.01 id=year;
run;