R6 Class Representing PosteriorBVARPANEL
Source:R/specify_bvarpanel.R
specify_posterior_bvarPANEL.RdThe class PosteriorBVARPANEL 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 BVARPANEL 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
Method new()
Create a new posterior output PosteriorBVARPANEL.
Usage
specify_posterior_bvarPANEL$new(specification_bvarPANEL, posterior_bvarPANEL)Method get_posterior()
Returns a list containing Bayesian estimation output.
Examples
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
posterior$get_posterior()
Method get_last_draw()
Returns an object of class BVARPANEL with the last draw of the current
MCMC run as the starting value to be passed to the continuation of the
MCMC estimation using estimate().
Examples
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
burn_in = estimate(specification, 5)
posterior = estimate(burn_in, 5)
Examples
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
class(posterior)
#> [1] "PosteriorBVARPANEL" "R6"
## ------------------------------------------------
## Method `specify_posterior_bvarPANEL$get_posterior`
## ------------------------------------------------
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
posterior$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
#>
#> $A
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.0547213 1.0011152 0.3886203 -0.1689910
#> [2,] 0.1537751 0.7964868 0.4413507 -1.0377214
#> [3,] 0.7342987 -0.1178609 0.1491472 0.9195905
#> [4,] 1.2145557 -1.1369699 -0.3437289 0.3108160
#> [5,] -0.9758545 -3.0698201 3.7115541 -1.0192800
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.04842591 0.1043002 0.3636906 0.1096719
#> [2,] 0.02722788 0.7369590 0.2863162 0.4674912
#> [3,] 0.13712078 -0.4573414 1.3470631 0.7055137
#> [4,] -0.03289211 0.7956617 -0.4546729 0.2503214
#> [5,] -0.30129004 3.3446949 0.8358000 -2.8982320
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9912965 0.1234523 1.01532133 1.2350210
#> [2,] 0.1865770 0.4008763 0.36635538 0.8146273
#> [3,] 0.3509388 0.2533579 0.08214285 0.4304927
#> [4,] -0.2162185 0.2777162 -0.55295544 -0.4052303
#> [5,] -1.2394291 -0.1295821 -4.51353747 -9.8495717
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0317291 -0.3455629 0.88181287 0.67669021
#> [2,] 0.0739439 0.1428560 -0.03758556 0.07942182
#> [3,] 0.4809623 0.2528161 0.78093714 1.09360035
#> [4,] -0.2939819 -0.2495128 0.22590878 0.06424030
#> [5,] -1.4644017 1.9693086 -3.32770068 -7.66088910
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9571749 -0.17584718 0.3597657 0.2826820
#> [2,] 0.1922557 0.02301838 -0.2279268 -0.2851994
#> [3,] 0.3313363 0.05244055 1.1898552 1.3482630
#> [4,] -0.3325007 0.43001905 0.1024194 0.4372704
#> [5,] -1.5015065 1.65839330 0.2809852 -4.7187698
#>
#>
#> $V
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6.038322 -1.549037 3.9242254 -0.7537020 -2.4774025
#> [2,] -1.549037 7.762418 -3.6547881 -1.3101571 2.1398858
#> [3,] 3.924225 -3.654788 11.6142067 0.1425780 0.1000343
#> [4,] -0.753702 -1.310157 0.1425780 6.3341872 -0.6650445
#> [5,] -2.477402 2.139886 0.1000343 -0.6650445 65.0520238
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 2.1206110 -0.1778616 -0.2963519 0.6596142 -5.256294
#> [2,] -0.1778616 1.8866786 0.8621101 -0.6507849 -0.941649
#> [3,] -0.2963519 0.8621101 2.5445044 -0.9037008 1.829624
#> [4,] 0.6596142 -0.6507849 -0.9037008 2.3356029 3.893467
#> [5,] -5.2562938 -0.9416490 1.8296237 3.8934666 110.790927
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 2.7525623 -0.2710912 -1.1372370 1.180295 -13.345453
#> [2,] -0.2710912 2.0992037 0.8736468 -1.012141 1.236340
#> [3,] -1.1372370 0.8736468 2.8401346 -1.185612 7.399803
#> [4,] 1.1802953 -1.0121413 -1.1856118 2.152752 -5.752268
#> [5,] -13.3454530 1.2363399 7.3998034 -5.752268 113.493766
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 2.5783176 -1.463190 -0.4920804 1.080771 -8.2689368
#> [2,] -1.4631899 2.952948 1.0537463 -1.715427 6.5661873
#> [3,] -0.4920804 1.053746 2.4709014 -2.086522 0.9461897
#> [4,] 1.0807707 -1.715427 -2.0865225 4.239014 -2.6000064
#> [5,] -8.2689368 6.566187 0.9461897 -2.600006 103.1226976
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.5804420 -1.0447937 0.7663947 0.5824353 -4.659648
#> [2,] -1.0447937 4.8112076 -0.1096759 -3.2358793 1.926215
#> [3,] 0.7663947 -0.1096759 4.7665746 -1.0175081 -8.627714
#> [4,] 0.5824353 -3.2358793 -1.0175081 4.9904949 3.627432
#> [5,] -4.6596484 1.9262153 -8.6277143 3.6274322 65.582791
#>
#>
#> $Sigma
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 13.6543650 2.9687889 0.6769788 2.9172183
#> [2,] 2.9687889 8.8061536 0.7794571 0.1691061
#> [3,] 0.6769788 0.7794571 12.6237052 -5.4651692
#> [4,] 2.9172183 0.1691061 -5.4651692 13.4709913
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 3.9439626 0.66905910 0.3829912 -0.30615472
#> [2,] 0.6690591 10.09900397 -5.6028557 -0.01287639
#> [3,] 0.3829912 -5.60285567 10.7288090 3.56713623
#> [4,] -0.3061547 -0.01287639 3.5671362 7.29411900
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.96908282 0.06822501 0.1274209 0.1157919
#> [2,] 0.06822501 10.17591306 -6.7298238 -1.8421220
#> [3,] 0.12742086 -6.72982381 14.3881437 12.2344584
#> [4,] 0.11579186 -1.84212197 12.2344584 14.3080258
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5825404 0.1621063 -0.1950292 -0.1430187
#> [2,] 0.1621063 7.3362108 -1.5012659 3.7789656
#> [3,] -0.1950292 -1.5012659 10.7881774 10.4793250
#> [4,] -0.1430187 3.7789656 10.4793250 14.4646318
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.220124422 0.07902183 -0.05300057 -0.005438102
#> [2,] 0.079021828 6.36670365 -2.82365375 0.788069310
#> [3,] -0.053000569 -2.82365375 6.70401690 5.678569618
#> [4,] -0.005438102 0.78806931 5.67856962 7.023868186
#>
#>
#> $nu
#> [,1]
#> [1,] 5.099570
#> [2,] 5.099574
#> [3,] 5.099834
#> [4,] 5.099584
#> [5,] 5.099502
#>
#> $m
#> [,1]
#> [1,] 0.9238091
#> [2,] 3.3186766
#> [3,] 0.4884743
#> [4,] 0.8118063
#> [5,] 1.0846734
#>
#> $w
#> [,1]
#> [1,] 166.27814
#> [2,] 21.18025
#> [3,] 20.71281
#> [4,] 47.67367
#> [5,] 35.46234
#>
#> $s
#> [,1]
#> [1,] 0.6234268
#> [2,] 0.8451490
#> [3,] 0.9329487
#> [4,] 1.5443822
#> [5,] 0.5584622
#>
#> $scale
#> [,1]
#> [1,] 0.01427928
#> [2,] 0.01427928
#> [3,] 0.01580739
#> [4,] 0.01795151
#> [5,] 0.02002019
#>
#> $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,] 0.07545955 0.02799409 0.02768113 0.0295711
#> [2,] 0.02799409 0.17495367 -0.15065655 -0.1001737
#> [3,] 0.02768113 -0.15065655 0.46584753 0.4275734
#> [4,] 0.02957110 -0.10017367 0.42757343 0.5204795
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.07586903 -0.01517507 0.01045488 0.04853319
#> [2,] -0.01517507 0.16405675 -0.08568822 0.01094291
#> [3,] 0.01045488 -0.08568822 0.29295672 0.20897507
#> [4,] 0.04853319 0.01094291 0.20897507 0.32167674
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.04665292 -0.1689787 0.1853582 0.09563441
#> [2,] -0.16897873 10.3169246 -7.0793941 -0.18958548
#> [3,] 0.18535822 -7.0793941 6.3588746 1.99619826
#> [4,] 0.09563441 -0.1895855 1.9961983 2.60334847
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.067433988 0.005577417 -0.008318276 -0.01866694
#> [2,] 0.005577417 0.219122432 -0.183817308 -0.06159234
#> [3,] -0.008318276 -0.183817308 0.419886770 0.23611878
#> [4,] -0.018666938 -0.061592341 0.236118785 0.30180359
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.05313276 -0.0205076 0.0501001 0.02895634
#> [2,] -0.02050760 3.0442211 -2.5918321 -0.83679991
#> [3,] 0.05010010 -2.5918321 3.0252043 1.50476283
#> [4,] 0.02895634 -0.8367999 1.5047628 1.12538796
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.020762985 0.007107044 0.008592106 0.02081483
#> [2,] 0.007107044 0.138012885 -0.105824779 -0.03626081
#> [3,] 0.008592106 -0.105824779 0.283422469 0.27728272
#> [4,] 0.020814828 -0.036260815 0.277282720 0.34558777
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.023122818 0.007931739 0.009787947 0.02380239
#> [2,] 0.007931739 0.179807066 -0.078101770 0.05988272
#> [3,] 0.009787947 -0.078101770 0.272421986 0.24724140
#> [4,] 0.023802394 0.059882719 0.247241398 0.36528722
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02470659 -0.1818714 0.08268883 -0.02930086
#> [2,] -0.18187142 8.2681762 -4.61982094 0.81183951
#> [3,] 0.08268883 -4.6198209 4.78037523 2.11289923
#> [4,] -0.02930086 0.8118395 2.11289923 3.16373387
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.043362214 0.001296733 0.07092827 0.05851071
#> [2,] 0.001296733 0.345072987 -0.32505572 -0.07659054
#> [3,] 0.070928274 -0.325055719 0.67192581 0.39036796
#> [4,] 0.058510709 -0.076590538 0.39036796 0.32003222
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01548165 -0.1051558 0.1325592 0.07284846
#> [2,] -0.10515583 3.1230427 -2.6752624 -0.93653867
#> [3,] 0.13255920 -2.6752624 3.4669743 2.15323318
#> [4,] 0.07284846 -0.9365387 2.1532332 1.87369585
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.008031649 -0.01225955 0.03275528 0.0333565
#> [2,] -0.012259546 0.24337438 -0.29418465 -0.2220911
#> [3,] 0.032755282 -0.29418465 0.84419670 0.8391153
#> [4,] 0.033356498 -0.22209106 0.83911527 0.8791052
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.015200529 -0.006629523 0.004535181 0.002427677
#> [2,] -0.006629523 0.084306133 -0.090825578 -0.031553587
#> [3,] 0.004535181 -0.090825578 0.359162449 0.341020262
#> [4,] 0.002427677 -0.031553587 0.341020262 0.379638960
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.008854896 -0.1060541 0.05094342 -0.01684059
#> [2,] -0.106054094 8.8817643 -5.26756893 0.50547126
#> [3,] 0.050943419 -5.2675689 5.06052632 1.93063420
#> [4,] -0.016840587 0.5054713 1.93063420 2.64314985
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.018777498 0.02521261 -0.008260273 0.01511445
#> [2,] 0.025212614 0.33100809 -0.259435014 -0.01636891
#> [3,] -0.008260273 -0.25943501 0.386611455 0.20179253
#> [4,] 0.015114448 -0.01636891 0.201792526 0.20220901
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.008524098 0.006467543 0.03711221 0.04435227
#> [2,] 0.006467543 3.612151114 -1.95732808 0.28735231
#> [3,] 0.037112209 -1.957328082 1.89944735 0.77896794
#> [4,] 0.044352269 0.287352308 0.77896794 1.07059773
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01083425 -0.00488906 0.01229831 0.01005002
#> [2,] -0.00488906 0.25594667 -0.22292256 -0.11890090
#> [3,] 0.01229831 -0.22292256 0.49945049 0.45101720
#> [4,] 0.01005002 -0.11890090 0.45101720 0.45375297
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.011773488 -0.007947164 0.001055345 -0.003781642
#> [2,] -0.007947164 0.134482338 -0.091603200 0.005771509
#> [3,] 0.001055345 -0.091603200 0.433308395 0.420073593
#> [4,] -0.003781642 0.005771509 0.420073593 0.488855954
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.00629746 -0.0943369 0.07460599 0.02151871
#> [2,] -0.09433690 10.4422588 -7.00530813 -0.34202651
#> [3,] 0.07460599 -7.0053081 6.27386609 2.12822269
#> [4,] 0.02151871 -0.3420265 2.12822269 2.32699505
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.0125263341 0.01793319 0.0007646853 0.01884592
#> [2,] 0.0179331875 0.18861928 -0.0985396621 0.04388159
#> [3,] 0.0007646853 -0.09853966 0.2610152138 0.18297934
#> [4,] 0.0188459198 0.04388159 0.1829793381 0.21891001
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.005668256 -0.04841758 0.06587599 0.0406161
#> [2,] -0.048417577 2.45654520 -2.03449183 -0.5853669
#> [3,] 0.065875991 -2.03449183 2.86002007 1.8021224
#> [4,] 0.040616097 -0.58536689 1.80212243 1.6181863
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.003921253 -0.00506538 0.003558762 0.002000788
#> [2,] -0.005065380 0.18764560 -0.164293751 -0.090271076
#> [3,] 0.003558762 -0.16429375 0.265526434 0.216241408
#> [4,] 0.002000788 -0.09027108 0.216241408 0.200770396
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.009326993 -0.004323111 -0.004022804 -0.007407951
#> [2,] -0.004323111 0.125671511 -0.093387480 -0.002649565
#> [3,] -0.004022804 -0.093387480 0.316061199 0.282057616
#> [4,] -0.007407951 -0.002649565 0.282057616 0.321685822
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.004893979 -0.1072876 0.06506559 -0.002163271
#> [2,] -0.107287584 8.7334638 -6.08385171 -0.578928019
#> [3,] 0.065065586 -6.0838517 7.23288074 3.993234481
#> [4,] -0.002163271 -0.5789280 3.99323448 4.367056470
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.007436078 0.01128222 0.01513059 0.02469121
#> [2,] 0.011282217 0.21519073 -0.10271088 0.05426623
#> [3,] 0.015130586 -0.10271088 0.36276246 0.28946830
#> [4,] 0.024691208 0.05426623 0.28946830 0.33509670
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.003716163 -0.06273252 0.0646346 0.03039409
#> [2,] -0.062732516 4.88556440 -3.7867803 -0.92361877
#> [3,] 0.064634602 -3.78678026 3.7308016 1.61242578
#> [4,] 0.030394095 -0.92361877 1.6124258 1.18648990
#>
#>
#> $A_c
#> , , 1, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7951399 0.19222991 -0.1766094 -0.08240888
#> [2,] 0.2768676 0.97041439 -0.1895989 -0.03780580
#> [3,] 0.4407640 0.03445327 1.1678339 0.76121282
#> [4,] -0.3466540 -0.04209212 -0.2170618 0.20470384
#> [5,] -0.2073462 -3.55292727 8.5868409 6.84601593
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9331941 -0.1434224 0.02543143 -0.2339639
#> [2,] 0.3948793 0.6958605 0.76867903 1.2982910
#> [3,] 0.5835126 -0.4420039 1.52999545 1.3485626
#> [4,] -0.5350795 0.4680768 -0.71807524 -0.3852944
#> [5,] -1.1019606 0.9661656 7.81311876 4.2950023
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8688097 1.80912392 -1.6413966 -0.67450394
#> [2,] 0.1942482 0.55398346 -0.2714796 -0.09442985
#> [3,] 0.3044295 0.09802151 0.3024498 0.17714478
#> [4,] -0.2725303 0.30508736 0.2728729 0.80591626
#> [5,] 0.9693944 -57.40399136 60.9301957 19.99815330
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.4867174 -0.08551156 0.7092865 1.0202022
#> [2,] -0.4774748 -1.06545111 0.3905677 -0.4238150
#> [3,] -0.5412942 -2.32791893 1.7775022 0.1431419
#> [4,] 0.4197400 2.35099281 -1.0626883 0.5234269
#> [5,] -3.3245378 1.22222322 3.8227491 0.2262905
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0700649 -2.27085444 1.98034615 0.6794674
#> [2,] 0.1175074 1.05446854 -0.08424423 0.6812901
#> [3,] 0.1765304 0.69651582 0.26978079 0.8468867
#> [4,] -0.1988507 0.05713483 -0.17144790 -0.2111918
#> [5,] -0.6065821 19.29235227 -2.55558327 1.9069329
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9503343 0.26620767 -0.453194959 -0.4862806
#> [2,] 0.1838326 0.96793171 0.007566778 0.5550218
#> [3,] 0.4861375 0.01306174 1.546612002 1.7526393
#> [4,] -0.4369944 -0.03801718 -0.523813156 -0.5612267
#> [5,] -0.7266905 -4.34318008 11.020860047 4.1547750
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9484641 -0.06302658 0.1232348 -0.0282580
#> [2,] 0.4411334 0.76738285 0.7884663 1.4591968
#> [3,] 0.5939642 -0.29289460 1.7238170 1.5776007
#> [4,] -0.5443241 0.33756959 -0.8014349 -0.5293505
#> [5,] -2.2979631 -1.87696910 -0.9131883 -7.1880328
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8371568 -0.8568902 1.1307920 0.3091552
#> [2,] 0.2131517 0.5496123 0.3999572 0.7673247
#> [3,] 0.3099926 0.2946021 1.0283127 1.2895507
#> [4,] -0.2762753 0.3357361 -0.4984553 -0.2030999
#> [5,] 1.3217322 -8.4808101 -3.6122837 -12.1156008
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0555121 -0.3154742 1.775677298 1.7746035
#> [2,] -0.4655328 -0.3894995 -0.410557373 -0.7658686
#> [3,] -0.5367638 -0.8706572 0.564210633 -0.1176430
#> [4,] 0.5243972 0.9111407 0.001845376 0.7179775
#> [5,] -0.3024689 6.7979476 -12.817333537 -14.0659562
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9456546 -0.8132553 0.457108482 -0.01769135
#> [2,] 0.1149492 1.2779437 -0.303923299 0.50685650
#> [3,] 0.1871798 0.9126950 0.053312745 0.62066936
#> [4,] -0.1800534 -0.1630685 0.004304307 -0.10682425
#> [5,] 1.0187964 -20.3685190 41.818599388 28.66234105
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9700638 0.315813995 -0.1204283 0.01663306
#> [2,] 0.2182546 0.861935322 -0.1285686 0.33751277
#> [3,] 0.5134751 -0.087314861 1.5427287 1.74780844
#> [4,] -0.4562355 -0.004664684 -0.6307154 -0.73589131
#> [5,] -1.7230189 -1.899552849 9.6490211 2.72581726
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8283088 -0.2068781 0.1809535 -0.1032628
#> [2,] 0.3868226 0.6756969 0.9957890 1.6234494
#> [3,] 0.5950023 -0.1895109 1.3700002 1.2897844
#> [4,] -0.5179007 0.2853759 -0.5763161 -0.3345825
#> [5,] -0.4768705 0.5858109 -0.3403380 -4.5349913
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9653023 -2.6964713 1.6584093 -0.23415688
#> [2,] 0.2029133 -0.2829474 0.7937376 0.59239206
#> [3,] 0.2997289 -0.6497958 1.4855449 1.10472271
#> [4,] -0.2584212 0.8718527 -0.7196501 -0.04294604
#> [5,] -1.9905291 62.2458517 -31.7245638 2.76378810
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.1709040 -0.7084155 1.9798269 1.6483096
#> [2,] -0.2765888 -0.6394294 -0.3162963 -0.8104200
#> [3,] -0.1999703 -1.2870302 0.7193716 -0.1963759
#> [4,] 0.1716024 1.4415876 -0.2226779 0.8174320
#> [5,] -1.9676612 8.4111846 -13.0871944 -12.5061863
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9998695 -1.72023468 1.8326949 0.8021207
#> [2,] 0.1580022 1.00746479 0.1990893 0.8936519
#> [3,] 0.2531663 0.18252954 1.0556760 1.2882226
#> [4,] -0.2267813 0.06677588 -0.4532371 -0.4417832
#> [5,] -1.6342927 31.61387391 -26.4415318 -13.3518051
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9792637 0.18396164 -0.31303517 -0.25932254
#> [2,] 0.2098993 0.92388922 0.04821615 0.54109774
#> [3,] 0.5009072 -0.16012184 1.71493115 1.89272067
#> [4,] -0.4507102 0.09110645 -0.65596693 -0.70993040
#> [5,] -1.6470794 -0.97016023 6.61140530 0.04804158
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9231371 -0.1307535 0.1714191 -0.007539436
#> [2,] 0.4178639 0.7000692 0.7562288 1.395357928
#> [3,] 0.5957997 -0.4307958 1.7325822 1.507544974
#> [4,] -0.5381048 0.4233577 -0.8496456 -0.534204697
#> [5,] -1.8488557 3.2336117 1.5210854 -1.788618259
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9666002 -1.89765652 1.175725 -0.2374391
#> [2,] 0.1957762 -0.06538634 1.019275 1.0658451
#> [3,] 0.2991987 -0.51180681 2.046531 1.9334247
#> [4,] -0.2511689 0.89008411 -1.245916 -0.6967567
#> [5,] -2.2930997 33.00370476 -21.390179 -7.2570457
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9776320 -0.3324337 1.1437074 0.9600168
#> [2,] -0.2477700 -0.6677470 -0.6911623 -1.2518561
#> [3,] -0.1494001 -1.4570090 0.2320640 -0.8854841
#> [4,] 0.1653062 1.4710369 0.5347470 1.7055456
#> [5,] -0.2536473 9.1379762 -11.8541079 -9.8459698
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9836899 -1.1937096 1.2425435 0.5153852
#> [2,] 0.1553210 1.0947199 0.2028556 0.9698881
#> [3,] 0.2470379 0.3512306 0.9087245 1.2365294
#> [4,] -0.2237731 0.0309184 -0.3898837 -0.4020226
#> [5,] -1.0030718 9.7670567 -6.4770690 -5.8707274
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9306164 0.36140953 -0.072106697 0.05982227
#> [2,] 0.2520790 0.86626981 0.006539374 0.47695382
#> [3,] 0.5252370 -0.14058404 1.744369158 1.91137307
#> [4,] -0.4440905 0.03531864 -0.730102167 -0.79494842
#> [5,] -2.1925730 -2.65375964 3.670586137 -3.44629107
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9189515 0.005633948 -0.3187583 -0.4504288
#> [2,] 0.4381160 0.699788770 0.6048253 1.2280032
#> [3,] 0.5751753 -0.230640259 1.6248196 1.5366089
#> [4,] -0.5214356 0.262213956 -0.6318707 -0.4136942
#> [5,] -2.0371057 -0.567088042 6.2261850 0.7128747
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9408366 0.49560684 -1.3630670 -1.39654650
#> [2,] 0.1947669 -0.04794405 0.6593284 0.69145290
#> [3,] 0.2914053 -0.72602670 1.4733146 1.13828872
#> [4,] -0.2518359 1.00127888 -0.7135960 -0.04093955
#> [5,] -1.2729483 -17.78780122 39.1670733 25.73186622
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0930934 0.1270212 0.5089519 0.8227126
#> [2,] -0.3268937 -0.6508104 -0.3933534 -0.9011497
#> [3,] -0.3607082 -1.5420398 0.7078100 -0.3993224
#> [4,] 0.3269622 1.4085836 0.1169669 1.1295016
#> [5,] 0.2930315 8.0229997 0.5479939 0.5751494
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9886354 -0.4961727 1.0032187 0.7614723
#> [2,] 0.1635907 0.8184925 0.7275498 1.3703858
#> [3,] 0.2788601 -0.1039623 2.0706846 2.2426101
#> [4,] -0.2496595 0.3497223 -1.3717051 -1.2913179
#> [5,] -1.3845025 -0.2762635 -9.4144454 -17.4351529
#>
#>
## ------------------------------------------------
## Method `specify_posterior_bvarPANEL$get_last_draw`
## ------------------------------------------------
specification = specify_bvarPANEL$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
#> **************************************************|