NAG Library Manual, Mark 29
Interfaces:  FL   CL   CPP   AD 

NAG CL Interface Introduction
Example description

nag_tsa_multi_autocorr_part (g13dbc) Example Program Results

Number of valid parameters =         3

Multivariate partial autocorrelations
      0.64498      0.92669      0.84300

Zero lag predictor error variance determinant
followed by error variance ratios
     0.00000      0.35502      0.02603      0.00409

Prediction error variances

Lag =    1
      0.00811     -0.00511      0.00159     -0.00029
     -0.00511      0.04089      0.00757      0.01843
      0.00159      0.00757      0.03834     -0.01894
     -0.00029      0.01843     -0.01894      0.06760

Lag =    2
      0.00354     -0.00087     -0.00075     -0.00105
     -0.00087      0.01946      0.00535      0.00566
     -0.00075      0.00535      0.01900     -0.01071
     -0.00105      0.00566     -0.01071      0.04058

Lag =    3
      0.00301     -0.00087     -0.00054      0.00065
     -0.00087      0.01824      0.00872      0.00247
     -0.00054      0.00872      0.00935     -0.00216
      0.00065      0.00247     -0.00216      0.02254

Last backward prediction error variances

Lag =    3
      0.00331     -0.00392     -0.00106      0.00592
     -0.00392      0.01890      0.00348     -0.00330
     -0.00106      0.00348      0.01003     -0.01054
      0.00592     -0.00330     -0.01054      0.03336

Prediction coefficients

Lag =    1
      0.81861      0.23399     -0.17097      0.09256
      0.06738     -0.48720     -0.14064      0.04295
      0.15036      0.11924     -0.36725     -0.42092
     -0.70971      0.02998      0.59779      0.34610

Lag =    2
     -0.34049     -0.13370      0.40610     -0.02183
     -1.27574     -0.13591     -0.65779     -0.11267
     -0.45439      0.19379      0.63420      0.33920
     -0.43237     -0.54848     -0.62897      0.16670

Lag =    3
      0.16437      0.13858      0.01290      0.03463
      0.39291      0.07407     -0.08802     -0.15361
     -1.29240     -0.24489      0.30235      0.39442
      0.89768     -0.39040      0.25151     -0.28304

Backward prediction coefficients

Lag =    1
      0.41541      0.06149      0.15319      0.05079
      0.12370     -0.26471     -0.22721      0.48503
     -0.86933     -0.47373      0.37924      0.13814
      1.30779     -0.09178     -1.45398     -0.21967

Lag =    2
     -0.06740     -0.12255     -0.13673     -0.09730
     -1.24801      0.03090      0.51706     -0.28925
      0.98045     -0.20194      0.16307     -0.10869
     -1.68389     -0.74589      0.52900      0.41580

Lag =    3
      0.03794      0.10491     -0.21635      0.08015
      0.75392      0.22603     -0.25661     -0.47450
     -0.00338      0.05636     -0.08818      0.12723
      0.55022     -0.41232      0.71649     -0.14565