nag_tsa_multi_inputmod_estim (g13bec) Example Program Results
Parameters to g13bec
____________________
nseries...................... 2
criteria............ Nag_Marginal cfixed................. Nag_FALSE
alpha.................. 1.00e-02 beta................... 1.00e+01
delta.................. 1.00e+03 gamma.................. 1.00e-07
print_level... Nag_Soln_Iter_Full
outfile................ stdout
Iter = -1 Residual = 6.456655e+03 Objf = 7.097184e+03
phi 0.000000e+00
stheta 0.000000e+00
omega series 1 2.000000e+00
delta series 1 5.000000e-01
constant 8.688399e+01
Iter = 0 Residual = 5.802775e+03 Objf = 6.378435e+03
phi 0.000000e+00
stheta 0.000000e+00
omega series 1 2.000000e+00
delta series 1 5.000000e-01
constant 8.573272e+01
Iter = 1 Residual = 2.354664e+03 Objf = 2.498647e+03
phi 6.589153e-01
stheta 6.571389e-02
omega series 1 3.721182e+00
delta series 1 5.237968e-01
constant 5.739128e+01
Iter = 2 Residual = 1.922339e+03 Objf = 2.032375e+03
phi 6.417690e-01
stheta -2.361191e-01
omega series 1 4.523132e+00
delta series 1 5.742824e-01
constant 3.814856e+01
Iter = 3 Residual = 1.530797e+03 Objf = 1.630603e+03
phi 5.550797e-01
stheta -3.097333e-01
omega series 1 7.697297e+00
delta series 1 7.358370e-01
constant -9.322197e+01
Iter = 4 Residual = 1.232926e+03 Objf = 1.324116e+03
phi 3.698329e-01
stheta -2.145294e-01
omega series 1 9.116523e+00
delta series 1 6.923742e-01
constant -9.985550e+01
Iter = 5 Residual = 1.200813e+03 Objf = 1.289272e+03
phi 3.889281e-01
stheta -2.649652e-01
omega series 1 8.906746e+00
delta series 1 6.659905e-01
constant -7.782515e+01
Iter = 6 Residual = 1.197922e+03 Objf = 1.286734e+03
phi 3.752731e-01
stheta -2.499956e-01
omega series 1 8.957172e+00
delta series 1 6.616140e-01
constant -7.656262e+01
Iter = 7 Residual = 1.197934e+03 Objf = 1.286623e+03
phi 3.804046e-01
stheta -2.594526e-01
omega series 1 8.954182e+00
delta series 1 6.599012e-01
constant -7.553429e+01
Iter = 8 Residual = 1.198009e+03 Objf = 1.286613e+03
phi 3.807082e-01
stheta -2.567453e-01
omega series 1 8.956063e+00
delta series 1 6.597438e-01
constant -7.549190e+01
Iter = 9 Residual = 1.197988e+03 Objf = 1.286612e+03
phi 3.808772e-01
stheta -2.580559e-01
omega series 1 8.955983e+00
delta series 1 6.596508e-01
constant -7.543851e+01
Iter = 10 Residual = 1.198002e+03 Objf = 1.286611e+03
phi 3.809218e-01
stheta -2.575832e-01
omega series 1 8.956106e+00
delta series 1 6.596484e-01
constant -7.544005e+01
Iter = 11 Residual = 1.197997e+03 Objf = 1.286611e+03
phi 3.809235e-01
stheta -2.577863e-01
omega series 1 8.956084e+00
delta series 1 6.596411e-01
constant -7.543552e+01
The number of iterations carried out is 11
The final values of the parameters and their standard deviations are
i para[i] sd
1 0.380924 0.166379
2 -0.257786 0.178178
3 8.956084 0.948061
4 0.659641 0.060239
5 -75.435521 33.505341
The residual sum of squares = 1.197997e+03
The objective function = 1.286611e+03
The degrees of freedom = 34.00
The correlation matrix is
1.0000 -0.1839 -0.1775 -0.0340 0.1394
-0.1839 1.0000 0.0518 0.2547 -0.2860
-0.1775 0.0518 1.0000 -0.3070 -0.2926
-0.0340 0.2547 -0.3070 1.0000 -0.8185
0.1394 -0.2860 -0.2926 -0.8185 1.0000
The residuals and the z and n values are
i res[i] z(t) noise(t)
1 0.397 180.567 -75.567
2 3.086 191.430 -72.430
3 -2.818 196.302 -77.302
4 -9.941 195.460 -86.460
5 -5.061 201.594 -84.594
6 14.053 199.076 -64.076
7 2.624 195.211 -69.211
8 -5.823 193.450 -81.450
9 -2.147 197.179 -81.179
10 -0.216 196.217 -74.217
11 -2.517 191.812 -76.812
12 7.916 184.544 -69.544
13 1.423 194.322 -72.322
14 11.936 200.369 -62.369
15 5.117 200.990 -65.990
16 -5.672 200.468 -75.468
17 -5.681 195.763 -80.763
18 -1.637 184.025 -76.025
19 -1.019 175.360 -75.360
20 -2.623 175.492 -79.492
21 3.283 182.162 -75.162
22 6.896 183.857 -68.857
23 5.395 190.797 -67.797
24 0.875 194.327 -72.327
25 -4.153 205.558 -77.558
26 6.206 204.261 -68.261
27 4.208 207.104 -67.104
28 -2.387 196.423 -74.423
29 -11.803 189.924 -87.924
30 6.435 175.158 -72.158
31 1.342 160.761 -71.761
32 -4.924 156.575 -79.575
33 4.799 164.256 -75.256
34 -0.074 167.783 -73.783
35 -6.023 184.483 -80.483
36 -6.427 193.055 -85.055
37 -2.527 199.390 -80.390
38 2.039 201.302 -75.302
39 0.243 195.695 -76.695
40 -3.166 183.738 -80.738