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,] -0.21102094 -0.59817688 -0.37343794 -0.3252091
#> [2,] 0.29479247 0.07813029 -0.67637211 0.5461679
#> [3,] -0.07028739 -0.06761494 0.42547816 -0.5939923
#> [4,] 0.09250135 -2.08876854 1.03006061 -0.5029481
#> [5,] 4.65273039 -1.08553070 -0.06249677 0.5603375
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5549592 -0.5979822 0.94335082 0.36930858
#> [2,] 0.4055926 0.8141558 0.62517777 1.00971932
#> [3,] 0.6527925 0.3129333 0.45109432 0.54477832
#> [4,] -0.3640230 -0.1505244 0.01906171 0.07253341
#> [5,] 4.3221029 -3.0418161 4.41746328 3.52824098
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7140733 -0.1386995 0.3738449 0.08701643
#> [2,] 0.4214097 0.6158159 0.3110532 0.63121468
#> [3,] 0.7636865 0.2419256 0.4474132 0.51632948
#> [4,] -0.6532447 -0.3289742 0.4672667 0.34548494
#> [5,] 5.2494293 -4.6399936 8.8206678 7.44068182
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6564202 0.3322361 -0.09506144 -0.05060036
#> [2,] 0.3457996 1.0008025 -0.04989293 0.67624268
#> [3,] 0.5991228 0.3464754 1.34076340 1.53674697
#> [4,] -0.5311832 -0.4893626 -0.22438594 -0.41285780
#> [5,] 3.5344065 -6.9098995 7.57173678 4.59375331
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6657533 0.15370085 -0.3170726 -0.3374872
#> [2,] 0.1897268 1.01617123 1.4835408 2.1940218
#> [3,] 0.5269268 0.25797374 1.1724086 1.2490647
#> [4,] -0.6199356 -0.02482425 -0.6975506 -0.5713343
#> [5,] 2.7507574 -7.66056237 11.1043696 6.6662394
#>
#>
#> $V
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 4.3706865 0.2965730 -0.33117557 -0.38860864 -4.6299917
#> [2,] 0.2965730 2.3853685 -0.10190517 0.44900457 -1.2534478
#> [3,] -0.3311756 -0.1019052 2.56093988 -0.05129898 1.6732285
#> [4,] -0.3886086 0.4490046 -0.05129898 4.36144105 -0.5031079
#> [5,] -4.6299917 -1.2534478 1.67322845 -0.50310794 39.7275400
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.10878855 -0.14564883 -0.4957657 -0.01856652 -0.7640366
#> [2,] -0.14564883 1.60657612 0.4561010 0.05367229 -0.6584377
#> [3,] -0.49576571 0.45610099 1.2759351 -0.24442120 1.5389693
#> [4,] -0.01856652 0.05367229 -0.2444212 1.49973660 -3.4782726
#> [5,] -0.76403662 -0.65843768 1.5389693 -3.47827256 47.0606146
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.3501290 -0.1702457 -1.6073265 0.9527629 -3.515178
#> [2,] -0.1702457 1.3276825 0.6786225 -0.2587889 1.238505
#> [3,] -1.6073265 0.6786225 6.3506508 -3.0703198 6.993161
#> [4,] 0.9527629 -0.2587889 -3.0703198 2.5693927 -2.824736
#> [5,] -3.5151781 1.2385047 6.9931613 -2.8247363 75.504251
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.1076878 0.1680254 -0.3512702 0.1464657 0.4255297
#> [2,] 0.1680254 1.5137887 1.0730098 -0.7083787 3.4616009
#> [3,] -0.3512702 1.0730098 3.2194354 -1.7364152 1.0682415
#> [4,] 0.1464657 -0.7083787 -1.7364152 1.7855113 -1.2930257
#> [5,] 0.4255297 3.4616009 1.0682415 -1.2930257 72.8047149
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 2.6352653 -0.823962009 0.381694738 -0.1434388 -1.760318
#> [2,] -0.8239620 4.526859965 -0.009657409 0.8737151 3.371616
#> [3,] 0.3816947 -0.009657409 7.069826622 -5.5673329 -13.253601
#> [4,] -0.1434388 0.873715127 -5.567332858 8.5452576 12.483190
#> [5,] -1.7603177 3.371616040 -13.253601224 12.4831904 89.839249
#>
#>
#> $Sigma
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 15.9858144 4.202563 -1.1434568 0.9598129
#> [2,] 4.2025633 15.068055 -5.6636452 -2.0420447
#> [3,] -1.1434568 -5.663645 10.5835250 0.4955069
#> [4,] 0.9598129 -2.042045 0.4955069 5.7709641
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 4.4703009 0.2248897 2.160326 2.631849
#> [2,] 0.2248897 7.2401475 -5.866892 -1.160012
#> [3,] 2.1603257 -5.8668917 14.064187 8.845690
#> [4,] 2.6318489 -1.1600118 8.845690 10.840761
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.0231442 0.1069567 1.192273 1.5494808
#> [2,] 0.1069567 10.3963802 -5.277404 0.8779304
#> [3,] 1.1922732 -5.2774037 16.028488 13.9594530
#> [4,] 1.5494808 0.8779304 13.959453 16.7010084
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7150429 0.4318641 0.4250336 0.8306437
#> [2,] 0.4318641 7.8105900 -0.9770071 4.3393319
#> [3,] 0.4250336 -0.9770071 8.8717937 8.6999977
#> [4,] 0.8306437 4.3393319 8.6999977 13.0047920
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.617498773 0.01856483 0.008769986 0.183023
#> [2,] 0.018564831 10.99890805 -4.236585346 2.717269
#> [3,] 0.008769986 -4.23658535 13.033097737 10.821903
#> [4,] 0.183023002 2.71726923 10.821902996 13.254675
#>
#>
#> $nu
#> [,1]
#> [1,] 5.100113
#> [2,] 5.100200
#> [3,] 5.100128
#> [4,] 5.100370
#> [5,] 5.100489
#>
#> $m
#> [,1]
#> [1,] 1.2075435
#> [2,] 0.2530813
#> [3,] -1.2273085
#> [4,] 1.1972278
#> [5,] 1.4999158
#>
#> $w
#> [,1]
#> [1,] 59.24092
#> [2,] 19.73919
#> [3,] 21.71618
#> [4,] 15.31682
#> [5,] 70.67521
#>
#> $s
#> [,1]
#> [1,] 0.5241626
#> [2,] 1.1395217
#> [3,] 2.0888522
#> [4,] 1.0375126
#> [5,] 1.1761258
#>
#> $scale
#> [,1]
#> [1,] 0.01427928
#> [2,] 0.01427928
#> [3,] 0.01671019
#> [4,] 0.01841954
#> [5,] 0.02040663
#>
#> $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,] 0.09088701 0.05372832 0.03261613 0.06777226
#> [2,] 0.05372832 0.40476269 -0.27081303 -0.09722487
#> [3,] 0.03261613 -0.27081303 0.48351332 0.34758105
#> [4,] 0.06777226 -0.09722487 0.34758105 0.37047224
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.12650240 0.07440359 0.04407724 0.06568729
#> [2,] 0.07440359 0.34131173 -0.08475882 0.11033536
#> [3,] 0.04407724 -0.08475882 0.35726222 0.30903321
#> [4,] 0.06568729 0.11033536 0.30903321 0.46096934
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.2000372 -0.8425424 0.6659865 0.1062414
#> [2,] -0.8425424 9.3761843 -7.0646359 -0.7956437
#> [3,] 0.6659865 -7.0646359 6.4777974 1.9499561
#> [4,] 0.1062414 -0.7956437 1.9499561 1.7575669
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.062467375 0.002259561 0.006493947 0.007937263
#> [2,] 0.002259561 0.340174254 -0.193089184 -0.008213239
#> [3,] 0.006493947 -0.193089184 0.305291968 0.174074317
#> [4,] 0.007937263 -0.008213239 0.174074317 0.194233161
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.04557142 -0.02040523 0.06599615 0.07693892
#> [2,] -0.02040523 2.67961979 -1.88115112 -0.25693623
#> [3,] 0.06599615 -1.88115112 2.57260477 1.65707113
#> [4,] 0.07693892 -0.25693623 1.65707113 1.85061980
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.036458979 0.02258997 -0.01767191 0.007038182
#> [2,] 0.022589967 0.31321352 -0.24682261 -0.082908798
#> [3,] -0.017671913 -0.24682261 0.34146549 0.229726121
#> [4,] 0.007038182 -0.08290880 0.22972612 0.224866338
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.08072826 -0.03646942 0.09463905 0.05944649
#> [2,] -0.03646942 0.23966343 -0.13743132 0.03733567
#> [3,] 0.09463905 -0.13743132 0.56372601 0.49692608
#> [4,] 0.05944649 0.03733567 0.49692608 0.57968928
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.1826826 -1.0020904 1.007822 0.4266981
#> [2,] -1.0020904 14.5600313 -9.995020 -0.6810484
#> [3,] 1.0078219 -9.9950196 9.266888 3.3367721
#> [4,] 0.4266981 -0.6810484 3.336772 3.4847440
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02255533 -0.02242141 0.04073694 0.03155567
#> [2,] -0.02242141 0.20634822 -0.20418928 -0.06792809
#> [3,] 0.04073694 -0.20418928 0.35883946 0.23594091
#> [4,] 0.03155567 -0.06792809 0.23594091 0.21871815
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02157271 -0.2159033 0.1805366 0.05399022
#> [2,] -0.21590333 5.1147834 -3.9346563 -0.87908713
#> [3,] 0.18053657 -3.9346563 3.8961582 1.64274856
#> [4,] 0.05399022 -0.8790871 1.6427486 1.23713909
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.029446876 0.01041838 -0.007959158 0.01413873
#> [2,] 0.010418381 0.18857578 -0.212140013 -0.13495768
#> [3,] -0.007959158 -0.21214001 0.487408953 0.42759328
#> [4,] 0.014138733 -0.13495768 0.427593282 0.42015561
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.032180204 0.01228987 0.004153454 0.009418213
#> [2,] 0.012289867 0.15523102 -0.108201008 0.005782880
#> [3,] 0.004153454 -0.10820101 0.377007208 0.314431673
#> [4,] 0.009418213 0.00578288 0.314431673 0.357700070
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.09958721 -0.6168613 0.3995401 -0.0257390
#> [2,] -0.61686134 8.2325686 -4.9952245 0.6020188
#> [3,] 0.39954009 -4.9952245 4.6754817 1.5268805
#> [4,] -0.02573900 0.6020188 1.5268805 2.2492189
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006304130 -0.008367482 0.01761131 0.01301292
#> [2,] -0.008367482 0.129134229 -0.12936694 -0.03297456
#> [3,] 0.017611309 -0.129366936 0.32711311 0.23963131
#> [4,] 0.013012924 -0.032974564 0.23963131 0.22921182
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.007681408 -0.05754646 0.08470505 0.05661266
#> [2,] -0.057546464 2.64071177 -2.56941181 -1.09449812
#> [3,] 0.084705050 -2.56941181 3.58426630 2.26152664
#> [4,] 0.056612657 -1.09449812 2.26152664 1.78185147
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.0201404061 -0.0001913856 -0.004547809 0.005258111
#> [2,] -0.0001913856 0.1502400039 -0.156813508 -0.104073155
#> [3,] -0.0045478088 -0.1568135077 0.389142865 0.368078123
#> [4,] 0.0052581107 -0.1040731553 0.368078123 0.382703594
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.025361536 -0.003032186 0.04270842 0.04093578
#> [2,] -0.003032186 0.140487491 -0.04470363 0.05404508
#> [3,] 0.042708418 -0.044703626 0.43832390 0.42490957
#> [4,] 0.040935780 0.054045082 0.42490957 0.49118485
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.074704971 -0.5180608 0.3484314 0.005871213
#> [2,] -0.518060751 10.6542304 -7.1417398 -0.139253598
#> [3,] 0.348431359 -7.1417398 6.3683662 1.977823864
#> [4,] 0.005871213 -0.1392536 1.9778239 2.277764057
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.007281320 -0.007699787 0.02736038 0.02397859
#> [2,] -0.007699787 0.204152255 -0.22635427 -0.08169442
#> [3,] 0.027360385 -0.226354273 0.51413983 0.36525213
#> [4,] 0.023978592 -0.081694420 0.36525213 0.32347486
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.008488123 -0.1203896 0.0753642 0.006284737
#> [2,] -0.120389611 4.1046598 -2.7457994 -0.325791034
#> [3,] 0.075364204 -2.7457994 2.4320226 0.868687523
#> [4,] 0.006284737 -0.3257910 0.8686875 0.741747368
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.0114286835 -0.009276493 -0.0002896081 0.0001645899
#> [2,] -0.0092764933 0.303370337 -0.2071480796 -0.0819938327
#> [3,] -0.0002896081 -0.207148080 0.3414787100 0.2741428866
#> [4,] 0.0001645899 -0.081993833 0.2741428866 0.2650678417
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.020296574 0.001896606 0.05603335 0.05507588
#> [2,] 0.001896606 0.166797399 -0.06964154 0.05075283
#> [3,] 0.056033348 -0.069641543 0.51240915 0.46681265
#> [4,] 0.055075877 0.050752826 0.46681265 0.51910283
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.03425534 -0.3824419 0.3241688 0.07721916
#> [2,] -0.38244192 11.8581982 -8.3981516 -0.58462907
#> [3,] 0.32416880 -8.3981516 7.6588481 2.41547971
#> [4,] 0.07721916 -0.5846291 2.4154797 2.38944591
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.003389598 -0.002812256 0.005561876 0.005008305
#> [2,] -0.002812256 0.173465281 -0.107028213 0.023605040
#> [3,] 0.005561876 -0.107028213 0.341304486 0.270268214
#> [4,] 0.005008305 0.023605040 0.270268214 0.300472360
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.004858786 -0.06788097 0.05512706 0.01672057
#> [2,] -0.067880973 4.03991468 -2.84949729 -0.43127191
#> [3,] 0.055127063 -2.84949729 2.81587658 1.20506503
#> [4,] 0.016720575 -0.43127191 1.20506503 1.05527320
#>
#>
#> $A_c
#> , , 1, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8971438 0.3140955 0.07004349 0.03297886
#> [2,] 0.1688465 0.9578926 -0.20447955 0.20920992
#> [3,] 0.6009857 0.3638863 1.11204106 1.23849071
#> [4,] -0.5898017 -0.4637757 -0.14314951 -0.20764598
#> [5,] 2.8314634 -0.7655076 2.02006134 0.86845966
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8746870 -0.35972746 0.3142496 -0.2089913
#> [2,] -0.3992081 0.16083393 -0.5074871 -0.2062736
#> [3,] -0.2618785 0.03682527 -0.3751887 -0.1700563
#> [4,] 0.2793350 0.28263143 1.1091756 1.1695540
#> [5,] 5.0805467 -1.56089775 3.7933455 6.4070070
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.2631432 -0.3647905 -0.1681786 -0.54812666
#> [2,] 0.2358082 2.4462158 -1.0847952 0.06762092
#> [3,] 0.4707159 2.8189682 -0.9355492 0.22570115
#> [4,] -0.4004516 -2.2221147 1.4592856 0.72282349
#> [5,] 13.2744879 -22.8304765 30.4461508 16.34790172
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7644661 -0.02832524 1.0071544 0.5210827
#> [2,] 0.3526489 0.66355717 0.1624848 0.8466925
#> [3,] 0.4627453 0.39191427 0.9317550 1.2236860
#> [4,] -0.3958581 -0.39355973 -0.2231178 -0.3830901
#> [5,] 1.1312480 2.42099740 -4.6089876 -1.2188342
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7087640 -2.0305565 1.9249729 0.6135991
#> [2,] 0.3835623 1.0941785 0.4484631 1.1780558
#> [3,] 0.6322349 0.5919052 1.3099149 1.6982677
#> [4,] -0.5714571 0.2608829 -1.1890946 -1.0708391
#> [5,] 4.2006549 5.2695268 -0.6637521 4.8869989
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7940176 -0.02662283 0.1226718 -0.01241014
#> [2,] 0.3166265 1.31997415 -0.4636882 0.11587241
#> [3,] 0.6368374 0.39555705 1.0168514 1.22976667
#> [4,] -0.5781730 -0.32256447 -0.1222330 -0.20259498
#> [5,] 1.8730732 -3.82298092 5.7164801 2.47413550
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0388670 0.06753551 0.5081901 0.3717961
#> [2,] -0.2456386 0.60267164 -0.3714335 0.1564396
#> [3,] -0.4732802 -0.30462025 -0.5419516 -0.7186913
#> [4,] 0.4390165 0.36270167 1.1707776 1.4346458
#> [5,] -0.2154654 -3.56412791 2.6963680 0.9839620
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.1961255 0.1930945 -0.577819058 -0.6356867
#> [2,] 0.6711173 1.9310254 0.003790147 0.9825868
#> [3,] 1.0553330 1.9518070 0.599607124 1.4710496
#> [4,] -0.9236613 -1.4715125 0.037547753 -0.4581715
#> [5,] 9.9179145 -29.7442943 31.027460031 11.8899927
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8051831 -0.3643006 0.9930806 0.5950391
#> [2,] 0.4322042 0.9341493 -0.1199625 0.6185563
#> [3,] 0.4554847 0.4260278 0.8404220 1.1529104
#> [4,] -0.4410754 -0.2169668 -0.2552981 -0.3869730
#> [5,] 3.8805791 -5.5397854 5.8641091 3.1213292
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6870127 -1.1469079 0.9783342 0.08165071
#> [2,] 0.3441814 0.8344007 0.6076998 1.09672137
#> [3,] 0.5615186 0.5097953 1.2232966 1.49943380
#> [4,] -0.5188451 0.1394403 -0.9351580 -0.75787723
#> [5,] 5.7788816 -3.3512532 11.8972403 11.66084392
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8769637 0.1461235 -0.11953838 -0.145989953
#> [2,] 0.2600067 1.0870284 -0.25992491 0.163776593
#> [3,] 0.6844983 0.2428378 0.94544364 1.059630471
#> [4,] -0.6538310 -0.2372424 0.04419289 0.006829769
#> [5,] 1.9201785 -3.2785942 5.17093110 3.011816363
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0120661 -0.04770097 0.5384060 0.35433127
#> [2,] -0.2507877 0.85147813 -0.6162671 0.04983095
#> [3,] -0.4103828 -0.26054511 -0.2319896 -0.41386061
#> [4,] 0.3567968 0.33023450 0.8291909 1.08785075
#> [5,] 2.8343258 -5.09806580 12.3657755 10.34837033
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.2230982 0.2491746 -0.3714732 -0.3524412
#> [2,] 0.6017311 -0.3102586 0.9563179 0.4105979
#> [3,] 0.9837704 -1.1205247 1.9679887 0.7635953
#> [4,] -0.8494283 1.2515232 -1.1878449 0.1619775
#> [5,] 9.5671533 -3.3821206 15.6004275 13.2296929
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8184101 0.05578072 -0.1806662 -0.29635296
#> [2,] 0.3885862 0.86533027 -0.3091150 0.32479367
#> [3,] 0.4424546 0.43979299 0.6363732 0.93627334
#> [4,] -0.4275824 -0.34851959 0.2405621 0.04088619
#> [5,] 3.5448159 -7.30525618 14.4567527 10.71245735
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7179351 -0.471646 0.1998361 -0.2985503
#> [2,] 0.4034411 -0.488164 1.6544390 1.3790039
#> [3,] 0.6784525 -2.159518 3.4017560 2.1113207
#> [4,] -0.6267563 2.469694 -2.9415328 -1.4069279
#> [5,] 4.5578585 -3.931743 25.0457753 24.8631249
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8911638 0.09375874 0.3371434 0.39103805
#> [2,] 0.2887420 1.16417638 -0.5192155 -0.06061967
#> [3,] 0.7303697 0.23365838 1.1424348 1.33661703
#> [4,] -0.6763009 -0.15552881 -0.3782066 -0.46031568
#> [5,] 0.4383135 -6.05206236 7.8629910 2.25870512
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0016295 0.1405117 -0.02419968 -0.1168356
#> [2,] -0.3109841 0.6845164 -0.87811712 -0.3333471
#> [3,] -0.3374328 -0.3670767 0.09669132 -0.1156938
#> [4,] 0.3034060 0.4419898 0.82197242 1.1433834
#> [5,] 3.4022388 -8.6731751 9.84737580 4.7136525
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.2374969 5.126673e-01 -0.4510771 -0.2856234
#> [2,] 0.6247982 1.744587e-04 1.4811475 1.1342283
#> [3,] 1.0028290 -8.189068e-01 2.8301145 1.8394949
#> [4,] -0.8660686 1.022130e+00 -1.8726405 -0.6785351
#> [5,] 8.8647633 -1.529117e+01 6.5747313 -3.4435890
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7360069 -0.1709031 0.7784424 0.50408374
#> [2,] 0.3004390 1.0574951 -0.2797602 0.49424714
#> [3,] 0.3851234 0.6389930 0.3833086 0.84182265
#> [4,] -0.3324352 -0.4585036 0.2200799 -0.06693018
#> [5,] 2.9444058 -8.3364625 9.6581995 4.53030968
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7727851 -1.0048411 0.4803025 -0.3170067
#> [2,] 0.3957259 -0.2899409 1.9074900 1.7932364
#> [3,] 0.6534294 -1.6056280 3.6827073 2.7959547
#> [4,] -0.6076577 2.0068440 -3.1207604 -1.9221022
#> [5,] 3.3757550 5.5297648 10.9700781 15.1445458
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9087799 0.3671482 -0.1526593 -0.04054195
#> [2,] 0.2689418 1.1054877 -0.2159701 0.26893012
#> [3,] 0.7440995 0.3623843 1.0187549 1.26897299
#> [4,] -0.6951708 -0.3457458 -0.1192564 -0.26302730
#> [5,] 0.4923534 -8.4326043 9.6510740 2.98525748
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9470284 0.2945046 0.06055425 0.06959869
#> [2,] -0.2360352 0.4842619 -0.73305095 -0.32673598
#> [3,] -0.2354566 -0.5284854 0.07093975 -0.26465889
#> [4,] 0.1970453 0.5902420 0.77689818 1.22030960
#> [5,] 5.2264553 -10.3199799 10.56173578 3.64473591
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6524039 1.137074 -1.184218 -0.6603663
#> [2,] 0.2579230 2.286400 -1.288821 -0.2584482
#> [3,] 0.3936466 2.759706 -1.429465 -0.2757007
#> [4,] -0.3543063 -1.878269 1.705315 1.1642535
#> [5,] 5.3482227 -73.811065 68.722046 23.7195495
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8577012 0.4324029 0.8581439 1.08848508
#> [2,] 0.4914353 1.4613483 -1.1523548 -0.06463597
#> [3,] 0.5635288 1.0947825 -0.5788243 0.18734307
#> [4,] -0.5407717 -1.1765485 1.2006484 0.39984366
#> [5,] 1.8946943 -4.3100349 6.5937842 3.75666479
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8497462 -1.1540608 0.9703627 0.1545162
#> [2,] 0.3501861 0.3053320 1.3109168 1.5219061
#> [3,] 0.5794834 -0.6890969 2.7186320 2.3253498
#> [4,] -0.5437042 1.2247895 -2.3093755 -1.5394278
#> [5,] 1.9345281 1.1718430 7.1680080 7.7792064
#>
#>
## ------------------------------------------------
## 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
#> **************************************************|