nag_tsa_multi_inp_model_forecast (g13bjc) Example Program Results

Parameters to g13bjc
____________________

nseries......................   6

cfixed.................. Nag_TRUE
outfile................    stdout

40 sets of observations were processed.

The residual mean square for the output series is    20.0902

The forecast values and their standard errors are


   i      fva      fsd

   1    93.398    4.4822
   2    96.958    6.1498
   3    86.046    7.0315
   4    77.589    7.2885
   5    82.139    7.3327
   6    96.276    7.5220
   7    98.345    8.0883
   8    93.577    8.8020

The values of z(t) and noise(t) are

   i       z1         z2         z3         z4         z5       noise

   1    -0.339     -3.889      0.000      0.000    188.603    -79.375
   2    -0.339     -0.000      4.514      0.000    199.438    -84.613
   3    -0.339     -0.000      0.000      2.479    204.683    -87.823
   4    -0.339      3.889     -4.514     -2.479    204.383    -91.940
   5    -0.678     -3.889      0.000      0.000    210.623    -89.056
   6    -0.678     -0.000      4.514      0.000    208.591    -77.426
   7    -0.678     -0.000      0.000      2.479    205.070    -80.870
   8    -0.678      3.889     -4.514     -2.479    203.407    -87.624
   9    -1.017     -3.889      0.000      0.000    206.974    -86.068
  10    -1.017     -0.000      4.514      0.000    206.132    -87.628
  11    -1.017     -0.000      0.000      2.479    201.920    -88.381
  12    -1.017      3.889     -4.514     -2.479    194.819    -75.698
  13    -1.356     -3.889      0.000      0.000    203.974    -76.729
  14    -1.356     -0.000      4.514      0.000    209.884    -75.041
  15    -1.356     -0.000      0.000      2.479    210.705    -76.828
  16    -1.356      3.889     -4.514     -2.479    210.373    -80.912
  17    -1.695     -3.889      0.000      0.000    205.942    -85.358
  18    -1.695     -0.000      4.514      0.000    194.575    -89.394
  19    -1.695     -0.000      0.000      2.479    185.866    -86.650
  20    -1.695      3.889     -4.514     -2.479    185.509    -84.709
  21    -2.035     -3.889      0.000      0.000    191.606    -78.682
  22    -2.035     -0.000      4.514      0.000    193.194    -80.673
  23    -2.035     -0.000      0.000      2.479    199.896    -77.340
  24    -2.035      3.889     -4.514     -2.479    203.497    -76.358
  25    -2.374     -3.889      0.000      0.000    214.552    -80.290
  26    -2.374     -0.000      4.514      0.000    213.770    -79.910
  27    -2.374     -0.000      0.000      2.479    216.796    -76.901
  28    -2.374      3.889     -4.514     -2.479    206.780    -79.302
  29    -2.713     -3.889      0.000      0.000    200.416    -91.814
  30    -2.713     -0.000      4.514      0.000    185.941    -84.742
  31    -2.713     -0.000      0.000      2.479    171.495    -82.261
  32    -2.713      3.889     -4.514     -2.479    166.673    -83.857
  33    -3.052     -3.889      0.000      0.000    173.418    -77.477
  34    -3.052     -0.000      4.514      0.000    176.573    -84.035
  35    -3.052     -0.000      0.000      2.479    192.594    -88.021
  36    -3.052      3.889     -4.514     -2.479    201.261    -87.105
  37    -3.391     -3.889      0.000      0.000    207.879    -81.599
  38    -3.391     -0.000      4.514      0.000    210.249    -85.372
  39    -3.391     -0.000      0.000      2.479    205.262    -85.350
  40    -3.391      3.889     -4.514     -2.479    193.874    -84.379
  41    -3.730     -3.889      0.000      0.000    185.617    -84.600
  42    -3.730      0.000      4.514      0.000    178.969    -82.795
  43    -3.730      0.000      0.000      2.479    169.607    -82.309
  44    -3.730      3.889     -4.514     -2.479    166.832    -82.409
  45    -4.069     -3.889      0.000      0.000    172.733    -82.636
  46    -4.069      0.000      4.514      0.000    178.579    -82.748
  47    -4.069      0.000      0.000      2.479    182.739    -82.804
  48    -4.069      3.889     -4.514     -2.479    183.582    -82.831