The class PosteriorBVARs contains posterior output and the specification
including the last MCMC draw for the Bayesian Panel VAR model.
Note that due to the thinning of the MCMC output the starting value in element
last_draw might not be equal to the last draw provided in
element posterior.
Public fields
last_drawan object of class BVARs with the last draw of the current MCMC run as the starting value to be passed to the continuation of the MCMC estimation using
estimate().posteriora list containing Bayesian estimation output.
Methods
PosteriorBVARs$new()
Create a new posterior output PosteriorBVARs.
PosteriorBVARs$get_posterior()
Returns a list containing Bayesian estimation output.
Examples
specification = specify_bvars$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
posterior$get_posterior()PosteriorBVARs$get_last_draw()
Returns an object of class BVARs with the last draw of the current
MCMC run as the starting value to be passed to the continuation of the
MCMC estimation using estimate().
Examples
specification = specify_bvars$new(
data = ilo_dynamic_panel[1:5]
)
burn_in = estimate(specification, 5)
posterior = estimate(burn_in, 5)Examples
specification = specify_bvars$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
class(posterior)
#> [1] "PosteriorBVARs" "R6"
## ------------------------------------------------
## Method `PosteriorBVARs$get_posterior()`
## ------------------------------------------------
specification = specify_bvars$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
posterior$get_posterior()
#> $A_c_cpp
#> [,1]
#> [1,] numeric,100
#> [2,] numeric,100
#> [3,] numeric,100
#> [4,] numeric,100
#> [5,] numeric,100
#>
#> $Sigma_c_cpp
#> [,1]
#> [1,] numeric,80
#> [2,] numeric,80
#> [3,] numeric,80
#> [4,] numeric,80
#> [5,] numeric,80
#>
#> $nu
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 5.100000 5.100000 5.100000 5.106178 5.106178
#> [2,] 5.100000 5.100000 5.209739 5.209739 5.209739
#> [3,] 5.100000 5.100000 5.100000 5.100000 5.100000
#> [4,] 5.100000 5.100000 5.100000 5.100000 5.100000
#> [5,] 5.085546 5.085546 5.085546 5.085546 5.068466
#>
#> $m
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.0289963 0.8535821 0.6970159 0.3890592 0.8146473
#> [2,] 0.8217636 0.8330153 0.6899908 0.7520781 0.9693726
#> [3,] 0.9755457 1.1156229 0.5802595 0.8064154 0.8901187
#> [4,] 0.2999274 0.5331938 0.8034993 0.5042762 0.9045823
#> [5,] 0.5226304 1.0350667 0.8140604 0.6697936 1.1975751
#>
#> $w
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.27047640 0.10664274 0.11075755 0.14920910 0.11074465
#> [2,] 0.19042605 0.10616340 0.05626761 0.04993345 0.05462572
#> [3,] 0.15857694 0.06563184 0.07750850 0.05794045 0.04352454
#> [4,] 0.04077182 0.11902268 0.15499282 0.29022811 0.50017510
#> [5,] 0.12783445 0.15907936 0.13336775 0.13952250 0.11402572
#>
#> $s
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 76.46972 56.93489 93.52144 50.48280 90.69067
#> [2,] 92.39225 72.22866 59.76586 64.97174 67.46900
#> [3,] 122.13724 37.40156 74.52211 39.73472 66.24010
#> [4,] 60.37953 69.51325 65.81671 48.38556 76.65872
#> [5,] 171.70783 36.34097 66.65888 49.74742 45.02938
#>
#> $scale
#> [,1]
#> [1,] 0
#> [2,] 0
#> [3,] 0
#> [4,] 0
#> [5,] 0
#>
#> $Y
#> [,1]
#> [1,] numeric,700
#> [2,] numeric,700
#> [3,] numeric,700
#> [4,] numeric,700
#> [5,] numeric,700
#>
#> $Sigma_c
#> , , 1, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.38063916 0.07975577 -0.7575409 -0.2925794
#> [2,] 0.07975577 2.12963902 0.2429499 -0.4573482
#> [3,] -0.75754094 0.24294990 3.9145953 0.4858633
#> [4,] -0.29257940 -0.45734817 0.4858633 2.5978330
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.767055208 0.006113813 -0.35801766 0.07198315
#> [2,] 0.006113813 1.353157270 0.06846622 -0.04375209
#> [3,] -0.358017662 0.068466221 3.15695155 0.83059338
#> [4,] 0.071983154 -0.043752088 0.83059338 2.63749874
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 4.947176 -3.0659855 1.318637 -2.3482371
#> [2,] -3.065986 22.8676340 -12.004410 0.8229033
#> [3,] 1.318637 -12.0044103 12.499140 2.5236414
#> [4,] -2.348237 0.8229033 2.523641 8.3075144
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.0508119 0.3526033 2.7497948 2.311220
#> [2,] 0.3526033 1.7423736 0.9103203 1.195142
#> [3,] 2.7497948 0.9103203 12.4825725 10.252710
#> [4,] 2.3112196 1.1951423 10.2527096 10.727403
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 4.5003004 -0.5562947 -0.7196324 -1.091342
#> [2,] -0.5562947 9.3275582 -2.4555408 -1.176918
#> [3,] -0.7196324 -2.4555408 8.5683839 2.095925
#> [4,] -1.0913416 -1.1769181 2.0959253 5.453734
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.6040674 0.6098616 -0.2612397 0.4195638
#> [2,] 0.6098616 2.1475453 0.2038837 0.5542554
#> [3,] -0.2612397 0.2038837 1.9724322 0.8830305
#> [4,] 0.4195638 0.5542554 0.8830305 2.0441962
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.42077912 -0.5220004 0.7552795 -0.06424595
#> [2,] -0.52200042 2.0392099 -0.8506513 -0.21995773
#> [3,] 0.75527953 -0.8506513 2.6242244 1.18698150
#> [4,] -0.06424595 -0.2199577 1.1869815 4.26578476
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 3.3298779 -3.834975 0.1698808 -2.033179
#> [2,] -3.8349750 20.059188 -10.0082037 4.558986
#> [3,] 0.1698808 -10.008204 10.2063508 2.082259
#> [4,] -2.0331794 4.558986 2.0822588 6.294620
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.3819553 -0.33854259 0.48883528 0.3735411
#> [2,] -0.3385426 2.51751253 -0.06162183 0.4297931
#> [3,] 0.4888353 -0.06162183 6.37485819 4.4927513
#> [4,] 0.3735411 0.42979314 4.49275128 6.3275415
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9284192 -0.2844311 0.3280344 0.3705217
#> [2,] -0.2844311 3.4893081 -1.7226758 -0.1438894
#> [3,] 0.3280344 -1.7226758 3.5674124 2.0286979
#> [4,] 0.3705217 -0.1438894 2.0286979 4.0958907
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.1202113 -0.1126960 0.7858960 0.3888058
#> [2,] -0.1126960 1.9979459 -0.3974881 -0.3922411
#> [3,] 0.7858960 -0.3974881 3.8907565 0.5233476
#> [4,] 0.3888058 -0.3922411 0.5233476 2.3502113
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.68876535 -0.6117002 -0.3761843 -0.03179762
#> [2,] -0.61170018 2.6043277 -0.2646078 0.36609274
#> [3,] -0.37618432 -0.2646078 2.1616395 0.41102523
#> [4,] -0.03179762 0.3660927 0.4110252 2.27445039
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.58093496 -0.5374299 -0.02292843 -0.5497016
#> [2,] -0.53742991 10.1556569 -5.58636403 -0.1331992
#> [3,] -0.02292843 -5.5863640 6.44396031 2.6764582
#> [4,] -0.54970160 -0.1331992 2.67645819 6.5396334
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.9933695 -0.5711376 1.0772343 1.099866
#> [2,] -0.5711376 2.5002482 -0.2907189 -1.034971
#> [3,] 1.0772343 -0.2907189 5.4629052 3.232124
#> [4,] 1.0998663 -1.0349705 3.2321245 5.646579
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.795839492 0.4388906 0.009050561 -0.8849924
#> [2,] 0.438890626 5.2722956 -2.551265342 -1.1445592
#> [3,] 0.009050561 -2.5512653 4.089824560 1.4773524
#> [4,] -0.884992357 -1.1445592 1.477352382 3.3768272
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.068140674 0.002719958 -0.04659786 0.11377952
#> [2,] 0.002719958 2.065799993 -0.29302871 0.08074243
#> [3,] -0.046597859 -0.293028712 1.84731277 0.72081421
#> [4,] 0.113779518 0.080742426 0.72081421 2.95414922
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.8118943 -0.1699378 0.1184069 -0.3818873
#> [2,] -0.1699378 2.8109138 -0.7697505 0.9236656
#> [3,] 0.1184069 -0.7697505 3.0842434 0.1090868
#> [4,] -0.3818873 0.9236656 0.1090868 3.0873390
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.781636 1.449414 -1.708957 -0.026046
#> [2,] 1.449414 14.989135 -11.628939 -1.044324
#> [3,] -1.708957 -11.628939 13.012485 3.161335
#> [4,] -0.026046 -1.044324 3.161335 2.951803
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.59790651 0.08508404 0.6283869 0.7742658
#> [2,] 0.08508404 1.18974862 0.2654839 0.5890063
#> [3,] 0.62838693 0.26548389 3.3269535 1.2346060
#> [4,] 0.77426585 0.58900625 1.2346060 2.5887039
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.6659938 -0.3630282 -0.1788386 0.143073
#> [2,] -0.3630282 4.4470981 -1.0519553 0.263626
#> [3,] -0.1788386 -1.0519553 5.8228441 2.763137
#> [4,] 0.1430730 0.2636260 2.7631371 4.586752
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.0707945 0.45103806 -0.53376936 -0.20694249
#> [2,] 0.4510381 2.99770161 -0.90796266 0.02620834
#> [3,] -0.5337694 -0.90796266 3.08487658 -0.02206695
#> [4,] -0.2069425 0.02620834 -0.02206695 2.90252593
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.58778919 -0.08333205 0.12323727 -0.25647041
#> [2,] -0.08333205 2.14390317 -0.56289329 0.50771992
#> [3,] 0.12323727 -0.56289329 2.04670549 0.01161477
#> [4,] -0.25647041 0.50771992 0.01161477 2.41416554
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.94429735 -0.00882417 -0.3000349 -0.1720077
#> [2,] -0.00882417 11.94623754 -8.2602046 -0.7631309
#> [3,] -0.30003491 -8.26020464 10.2537066 3.1240098
#> [4,] -0.17200767 -0.76313087 3.1240098 5.3281434
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.629049724 -0.09497637 0.09722493 0.001401665
#> [2,] -0.094976375 2.48772725 0.32275740 0.054859855
#> [3,] 0.097224925 0.32275740 4.05329871 1.632209950
#> [4,] 0.001401665 0.05485986 1.63220995 3.975444865
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.41301227 -0.9074634 0.7064922 0.03973047
#> [2,] -0.90746336 6.5510124 -2.7522814 -1.17684668
#> [3,] 0.70649219 -2.7522814 4.5797663 1.57868573
#> [4,] 0.03973047 -1.1768467 1.5786857 2.63763922
#>
#>
#> $A_c
#> , , 1, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.1904722 0.1591577 0.8345344 0.2847645
#> [2,] -0.1129768 1.0413150 -0.9643392 -0.4539323
#> [3,] 0.1772130 0.3897294 -0.3257642 -0.3126453
#> [4,] -0.1827119 -0.3676608 0.9509539 1.2385780
#> [5,] -2.1561013 -3.0319235 1.2740636 -0.6869625
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8492155 0.2485910 0.3805800 0.1156576
#> [2,] 0.3699895 0.8689060 0.3285513 0.5088825
#> [3,] 0.2712818 0.4177077 0.2516721 0.3160693
#> [4,] -0.2833968 -0.4216579 0.4403845 0.5908548
#> [5,] 2.3537627 1.1975806 -0.2640185 -0.3867979
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.4259856 0.23473540 0.86513324 1.1023376
#> [2,] 0.5902545 0.08643897 -0.09719322 -0.8806646
#> [3,] 1.0358117 -0.17415806 0.45705678 -1.3264730
#> [4,] -0.7642743 0.21661740 0.16529408 1.9027562
#> [5,] -2.3533047 5.29498104 -1.04004117 1.3464683
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.2849396 0.1601185 3.062837 2.7646129
#> [2,] -0.2014341 0.5718334 -1.137835 -0.9409509
#> [3,] -0.6098928 -0.2224868 -1.684609 -1.8949740
#> [4,] 0.4829370 0.1625927 1.547943 1.8711034
#> [5,] 1.5864012 1.0943517 5.022359 5.0695637
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0293564 -0.5961135 0.8156619 0.6822632
#> [2,] 0.1221348 0.7468151 0.2188828 0.5675937
#> [3,] 0.3279178 -0.2273412 1.0523143 0.9373368
#> [4,] -0.2776871 0.5157691 -0.4402140 -0.2268625
#> [5,] -3.0094618 0.3919018 -0.6154629 -1.1147663
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.03962861 -0.13354568 0.6379359 0.184352245
#> [2,] -0.05865501 1.22207423 -0.4184792 -0.005366688
#> [3,] 0.51879491 0.35985100 1.0315742 0.865457054
#> [4,] -0.47809014 -0.29372737 -0.3020742 0.110035607
#> [5,] -0.23869443 0.06916549 1.4188056 0.257778274
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.26444259 -0.04067502 -0.1122525 -0.62350204
#> [2,] 0.08489094 0.46766335 0.2960173 -0.08158275
#> [3,] 0.04153940 -0.10272571 1.2758070 0.45124606
#> [4,] -0.14698930 0.20650860 -0.2779951 0.80990510
#> [5,] 0.73498495 0.24521588 1.7774734 2.77751640
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.4047419 0.27741717 0.91624454 1.0752044
#> [2,] 0.4082616 -0.08554255 0.04332071 -0.7599594
#> [3,] 0.7268281 -0.83191157 0.47436305 -0.9755448
#> [4,] -0.4776899 0.78627116 0.12350463 1.5847179
#> [5,] -0.5700397 5.04938558 -2.15967589 1.5747441
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9803531 0.07182301 1.406514 1.3830426
#> [2,] -0.2711069 0.78451535 -2.081052 -1.4436250
#> [3,] -0.6183273 -0.34805289 -1.801516 -2.2111003
#> [4,] 0.5818901 0.31304358 2.294028 2.7442523
#> [5,] 2.2155502 1.05347380 2.256183 -0.5928071
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9912564 -0.0351604 -0.1835146 -0.25636961
#> [2,] 0.1330905 0.6677770 0.3044381 0.71552340
#> [3,] 0.2041601 -0.3639229 1.4675599 1.16400199
#> [4,] -0.2377413 0.4605281 -0.4207632 -0.02245861
#> [5,] 1.8751730 -3.4405096 1.7995061 -2.03489401
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9439659 0.4650860 -0.36232585 -0.18554787
#> [2,] -0.1230928 0.6056309 0.19487806 0.07513690
#> [3,] -0.1216556 -0.6156093 1.08841597 1.03327541
#> [4,] 0.1472111 0.4247783 0.03406354 0.07225753
#> [5,] 0.5942666 -0.6657438 1.11053359 2.76190734
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.596450607 -0.09615341 0.2276953 0.191458340
#> [2,] 0.188676208 0.32828104 0.3822429 -0.044237755
#> [3,] 0.008391821 0.12489149 0.6648055 0.128319324
#> [4,] 0.077165884 0.06533606 0.1338210 0.838197961
#> [5,] 0.680025763 0.67971711 -1.0585903 0.002954144
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.99587097 -0.7237703 1.1018332 0.19275844
#> [2,] 0.08162849 0.8011103 -0.2667544 -0.04203466
#> [3,] 0.08906443 0.6052641 0.2453935 0.25201472
#> [4,] -0.11202640 -0.1873809 0.3037539 0.70937395
#> [5,] 0.98037862 0.4808391 -1.4868695 0.34945376
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5196080 0.1398914 0.9542838 1.504616
#> [2,] -0.2915476 0.6915568 -1.6607134 -2.122659
#> [3,] -0.7787412 -0.2726748 -1.9443425 -1.989939
#> [4,] 0.9308137 0.2259336 2.6071964 2.528791
#> [5,] 0.1585308 0.6388086 -0.9058733 -3.045869
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.62612595 0.03829009 0.1518379 0.70118631
#> [2,] 0.11649849 0.36823521 0.5741648 0.43953633
#> [3,] 0.25476940 -0.57490224 1.7002691 0.68855956
#> [4,] -0.08420946 0.64795878 -0.7693021 -0.04789843
#> [5,] -0.18918404 -2.67369024 -1.2625415 2.76470844
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9104052997 0.5874340 -0.04454699 -0.07919669
#> [2,] -0.0249894401 0.4375063 0.04282932 0.22424009
#> [3,] 0.0688695356 -0.4675598 1.42924606 1.31792198
#> [4,] 0.0008630811 0.2593556 -0.34588632 -0.22179679
#> [5,] -0.7799850194 -0.8549209 -1.51858402 0.39709414
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.95727422 0.1373162 0.21073979 -0.3604906
#> [2,] 0.29834763 0.8890840 -0.09502563 -0.3376175
#> [3,] -0.01940086 0.3124704 0.22521006 -0.0807149
#> [4,] -0.03380927 -0.2433859 0.56425650 1.2462795
#> [5,] -0.10347919 -2.3827903 2.38954044 0.3923427
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8365849 -1.0006760 0.9632966 0.19784685
#> [2,] 0.2307466 0.9410368 -0.2766269 -0.10685783
#> [3,] 0.2697201 0.6775433 0.2418871 -0.01584053
#> [4,] -0.2481525 -0.2016047 0.3956382 0.95469146
#> [5,] 1.2144044 2.4090722 -3.3721199 0.54028781
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.2734838 -0.2489002 0.9492715 2.1561890
#> [2,] 0.1778982 0.9177652 -1.5118357 -0.6794479
#> [3,] -0.3027556 -0.1623053 -1.7463680 -1.4521868
#> [4,] 0.2059356 0.2270824 2.3626097 1.6534141
#> [5,] -0.7183706 1.4584305 3.1577183 3.5455884
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.77356569 -0.6729942 0.5788895 0.4334015
#> [2,] 0.01410300 0.4525924 0.4968346 0.6004597
#> [3,] 0.19827567 -0.4791546 1.4201289 0.8977872
#> [4,] -0.08256448 0.8613858 -0.6653227 -0.0991007
#> [5,] -0.16915865 -2.3965715 -3.3430035 -0.2243277
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.13407144 -0.84389186 0.28242015 0.6519701
#> [2,] 0.54628382 1.37131388 -0.15529804 -0.1029883
#> [3,] 0.24106668 -0.06082378 1.18712431 0.9203128
#> [4,] 0.09840496 0.38882996 -0.29143525 -0.1904468
#> [5,] 0.75092066 1.48208673 -0.05948568 1.6634488
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.62915785 0.03190645 -0.02113993 -0.1766041
#> [2,] -0.27812674 0.43064723 0.37661050 0.3444069
#> [3,] 0.16874296 0.32162184 1.02004982 0.2476794
#> [4,] 0.02372881 -0.15159443 -0.12743483 0.7663909
#> [5,] 1.18204996 -0.56590327 2.63523158 0.3753879
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8898730 -1.0293693 1.1067419 0.15545430
#> [2,] 0.2823068 1.0419195 -0.3223885 0.05029568
#> [3,] 0.3164992 1.0951398 -0.0862053 -0.02138164
#> [4,] -0.2718812 -0.5536804 0.5445603 0.95336351
#> [5,] -1.2794029 0.8293864 1.2811732 -1.00085225
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5458149 -0.5749867 1.574740 1.886278
#> [2,] -0.2258648 0.2079252 -1.897175 -1.196860
#> [3,] -0.5495698 -0.1423191 -1.723531 -1.584944
#> [4,] 0.6936754 0.3364794 2.233101 1.965282
#> [5,] 0.9015136 1.5372619 -4.559818 -2.198686
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.3791222 -0.7812241 0.8408929 0.4490999
#> [2,] -0.3855922 0.3709040 0.2846137 0.2511693
#> [3,] -0.6033430 -0.5986556 1.1120321 0.3779943
#> [4,] 0.4889129 0.9533179 -0.4944633 0.4003353
#> [5,] -2.8172770 2.2614867 -2.1297930 0.7746728
#>
#>
## ------------------------------------------------
## Method `PosteriorBVARs$get_last_draw()`
## ------------------------------------------------
specification = specify_bvars$new(
data = ilo_dynamic_panel[1:5]
)
burn_in = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
posterior = estimate(burn_in, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|