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
PosteriorBVARPANEL$new()
Create a new posterior output PosteriorBVARPANEL.
PosteriorBVARPANEL$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()PosteriorBVARPANEL$get_last_draw()
Returns an object of class BVARPANEL with the last draw of the current
MCMC run as the starting value to be passed to the continuation of the
MCMC estimation using estimate().
Examples
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
burn_in = estimate(specification, 5)
posterior = estimate(burn_in, 5)Examples
specification = specify_bvarPANEL$new(
data = ilo_dynamic_panel[1:5]
)
posterior = estimate(specification, 5)
#> **************************************************|
#> bpvars: Forecasting with Bayesian Panel VARs |
#> **************************************************|
#> Progress of the MCMC simulation for 5 draws
#> Every draw is saved via MCMC thinning
#> Press Esc to interrupt the computations
#> **************************************************|
class(posterior)
#> [1] "PosteriorBVARPANEL" "R6"
## ------------------------------------------------
## Method `PosteriorBVARPANEL$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,] -3.101861 2.4717740 -3.4113287 -4.711677
#> [2,] 1.074473 -5.7346986 2.2464140 7.725279
#> [3,] -6.722068 2.8974794 0.5807068 5.911780
#> [4,] -10.080887 0.9472938 -2.5703935 -4.356170
#> [5,] -16.545891 4.5665852 2.2150997 19.129094
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7310070 -0.06428756 0.2588496 0.1027316
#> [2,] -0.2428132 -0.51142666 1.5426785 1.3965642
#> [3,] -0.2083215 -1.62797420 2.2325211 1.3693015
#> [4,] 0.2548957 1.51074882 -1.0760026 -0.1061787
#> [5,] 6.0191328 9.33042960 4.9094479 7.4353788
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9341534 -0.5792319 0.05644837 -0.4802316
#> [2,] -0.2971947 1.3035567 -0.06774913 0.7824324
#> [3,] -0.1373208 1.6123463 1.47293406 2.9271638
#> [4,] 0.2007100 -1.1988449 -0.41618408 -1.4432013
#> [5,] 2.4289241 -3.4375891 15.51573201 7.4260140
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8448647 0.3939028 -0.4337285 -0.2308758
#> [2,] -0.3724110 -0.2160656 -0.1412543 -0.4504109
#> [3,] -0.3689082 -0.2779794 0.6032769 0.3104395
#> [4,] 0.3794825 0.1958716 0.1711403 0.4860617
#> [5,] 4.7347490 -10.6089414 25.1566877 12.8890528
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.84674726 0.05641097 -0.05403518 0.01874529
#> [2,] -0.07087738 1.05114109 -0.49197023 -0.06167609
#> [3,] -0.01986757 0.23200373 2.17599137 2.12195553
#> [4,] 0.10102712 -0.21169027 -0.94482248 -0.81591371
#> [5,] 6.32028095 -4.90991475 27.64557659 20.92082241
#>
#>
#> $V
#> , , 1
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 480.0808013 0.4080859 -71.19826 -100.93569 152.30095
#> [2,] 0.4080859 272.0927912 19.75102 60.67233 164.19123
#> [3,] -71.1982584 19.7510229 506.99047 50.07381 -34.69213
#> [4,] -100.9356890 60.6723297 50.07381 433.05810 556.16220
#> [5,] 152.3009517 164.1912262 -34.69213 556.16220 4317.70168
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 1.782967972 -0.3662845 0.001182646 0.117917 -39.389319
#> [2,] -0.366284495 8.1077894 10.788561123 -10.229146 -4.777994
#> [3,] 0.001182646 10.7885611 18.540685497 -17.245367 -32.752899
#> [4,] 0.117917036 -10.2291464 -17.245367276 17.344909 23.169941
#> [5,] -39.389319188 -4.7779937 -32.752898610 23.169941 1651.119692
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6.8832790 -0.9210524 -5.288933 5.481263 -43.01986
#> [2,] -0.9210524 8.3230088 10.061964 -9.426651 -23.71215
#> [3,] -5.2889330 10.0619644 21.650044 -18.918356 -42.70520
#> [4,] 5.4812626 -9.4266515 -18.918356 20.300747 31.67318
#> [5,] -43.0198624 -23.7121451 -42.705196 31.673182 1251.08556
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 5.808989 -10.160045 -11.82666 11.083959 -29.374586
#> [2,] -10.160045 33.475765 39.78309 -33.850987 7.778521
#> [3,] -11.826663 39.783088 54.01795 -43.641832 -29.315451
#> [4,] 11.083959 -33.850987 -43.64183 39.240706 -6.135903
#> [5,] -29.374586 7.778521 -29.31545 -6.135903 1239.386157
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 6.005181 -2.812321 -8.657881 10.05732 -7.400798
#> [2,] -2.812321 25.376519 28.684804 -26.61678 -72.163997
#> [3,] -8.657881 28.684804 55.011465 -52.19887 -140.556649
#> [4,] 10.057316 -26.616782 -52.198869 52.30450 126.969578
#> [5,] -7.400798 -72.163997 -140.556649 126.96958 1243.264035
#>
#>
#> $Sigma
#> , , 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 4.66680674 -0.42028601 -0.01459697 0.3135623
#> [2,] -0.42028601 3.78775253 -0.05360427 1.0843217
#> [3,] -0.01459697 -0.05360427 2.69169727 1.6189142
#> [4,] 0.31356226 1.08432174 1.61891416 4.8611760
#>
#> , , 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 2.1000274 -0.3974063 -0.1413494 -0.4209503
#> [2,] -0.3974063 8.9609306 -3.5164323 1.8055009
#> [3,] -0.1413494 -3.5164323 5.1147509 2.9258670
#> [4,] -0.4209503 1.8055009 2.9258670 5.3422352
#>
#> , , 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0075640 0.5239243 0.4939861 1.055792
#> [2,] 0.5239243 5.0255811 -1.0817996 2.518029
#> [3,] 0.4939861 -1.0817996 8.5490401 8.993216
#> [4,] 1.0557923 2.5180289 8.9932164 12.441472
#>
#> , , 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.47719269 -0.06205841 0.2610444 0.3821429
#> [2,] -0.06205841 3.78821693 -2.0931438 0.4725394
#> [3,] 0.26104444 -2.09314378 4.8476033 3.9603593
#> [4,] 0.38214291 0.47253944 3.9603593 5.0281087
#>
#> , , 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.2588828 -0.1707855 0.2352692 0.1443335
#> [2,] -0.1707855 3.6548882 -1.2696854 1.1679148
#> [3,] 0.2352692 -1.2696854 3.6626592 3.2912114
#> [4,] 0.1443335 1.1679148 3.2912114 4.6851409
#>
#>
#> $nu
#> [,1]
#> [1,] 5.100221
#> [2,] 5.100264
#> [3,] 5.100264
#> [4,] 5.100506
#> [5,] 5.100923
#>
#> $m
#> [,1]
#> [1,] 0.9431663
#> [2,] 2.2442621
#> [3,] 1.7067711
#> [4,] 1.6864638
#> [5,] 1.4379900
#>
#> $w
#> [,1]
#> [1,] 9426.68509
#> [2,] 12.53413
#> [3,] 42.65399
#> [4,] 37.63953
#> [5,] 31.63675
#>
#> $s
#> [,1]
#> [1,] 0.1876297
#> [2,] 0.4171976
#> [3,] 0.5780544
#> [4,] 0.4344424
#> [5,] 0.4614962
#>
#> $scale
#> [,1]
#> [1,] 0.01427928
#> [2,] 0.01427928
#> [3,] 0.01613942
#> [4,] 0.01810643
#> [5,] 0.02000144
#>
#> $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,] 0.0454262185 -0.0001065369 0.01966620 0.02071896
#> [2,] -0.0001065369 0.1199379535 -0.03941229 0.01381594
#> [3,] 0.0196661978 -0.0394122865 0.20533280 0.21168598
#> [4,] 0.0207189631 0.0138159367 0.21168598 0.26225859
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.020807934 -0.02046234 0.005545498 -0.007249765
#> [2,] -0.020462337 0.13258124 -0.106897208 -0.020066554
#> [3,] 0.005545498 -0.10689721 0.356619033 0.328453352
#> [4,] -0.007249765 -0.02006655 0.328453352 0.393609536
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.04874366 0.04661451 0.03280572 0.04487385
#> [2,] 0.04661451 5.54645659 -3.76448702 -0.23207572
#> [3,] 0.03280572 -3.76448702 4.25149679 2.09295775
#> [4,] 0.04487385 -0.23207572 2.09295775 2.28262162
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.03684258 -0.01586554 0.02386327 0.01315390
#> [2,] -0.01586554 0.17424931 -0.15013004 -0.01637942
#> [3,] 0.02386327 -0.15013004 0.31833395 0.17793289
#> [4,] 0.01315390 -0.01637942 0.17793289 0.17338792
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.04497923 -0.1230379 0.1083074 0.04882971
#> [2,] -0.12303794 3.1304673 -2.5425435 -0.78682081
#> [3,] 0.10830740 -2.5425435 2.5544312 1.20696975
#> [4,] 0.04882971 -0.7868208 1.2069698 0.88116844
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02180161 -0.01060116 -0.01530129 -0.02175895
#> [2,] -0.01060116 0.34105786 -0.21236737 -0.04567966
#> [3,] -0.01530129 -0.21236737 0.29121928 0.20793632
#> [4,] -0.02175895 -0.04567966 0.20793632 0.21432633
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.014914370 -0.02072194 0.02344332 0.006988174
#> [2,] -0.020721940 0.22044865 -0.13212231 0.044683215
#> [3,] 0.023443315 -0.13212231 0.39218038 0.354076558
#> [4,] 0.006988174 0.04468321 0.35407656 0.480216966
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02820459 -0.3135192 0.3440853 0.1551798
#> [2,] -0.31351921 10.8720924 -9.0327502 -2.1026501
#> [3,] 0.34408533 -9.0327502 9.7994126 4.4412774
#> [4,] 0.15517981 -2.1026501 4.4412774 3.5990386
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01863116 -0.01027801 0.0914225 0.0856947
#> [2,] -0.01027801 0.19882900 -0.1868063 -0.0383964
#> [3,] 0.09142250 -0.18680627 0.7867339 0.6596329
#> [4,] 0.08569470 -0.03839640 0.6596329 0.6489319
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01892810 -0.0504008 0.06009861 0.03502323
#> [2,] -0.05040080 2.2888710 -1.84818354 -0.50230312
#> [3,] 0.06009861 -1.8481835 2.01382264 0.99485890
#> [4,] 0.03502323 -0.5023031 0.99485890 0.78040168
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.0091278415 -0.0009111649 0.006128653 0.007544987
#> [2,] -0.0009111649 0.1565630209 -0.162731470 -0.099952321
#> [3,] 0.0061286527 -0.1627314697 0.358946980 0.316563287
#> [4,] 0.0075449874 -0.0999523214 0.316563287 0.305763507
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.008341869 -0.009974557 0.03060194 0.02785037
#> [2,] -0.009974557 0.121858419 -0.10118386 -0.01386245
#> [3,] 0.030601942 -0.101183861 0.39426697 0.39129504
#> [4,] 0.027850369 -0.013862450 0.39129504 0.46985671
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.03942466 -0.3354982 0.4888743 0.3141692
#> [2,] -0.33549824 7.8657457 -7.5633639 -2.7675855
#> [3,] 0.48887434 -7.5633639 9.8877424 5.7439001
#> [4,] 0.31416923 -2.7675855 5.7439001 4.6303168
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.015315807 -0.009563933 0.06577609 0.06231197
#> [2,] -0.009563933 0.113519026 -0.11856180 -0.03127345
#> [3,] 0.065776091 -0.118561796 0.63359561 0.55615856
#> [4,] 0.062311973 -0.031273449 0.55615856 0.54921068
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01038781 -0.06257914 0.08052966 0.04831003
#> [2,] -0.06257914 3.49882041 -2.55781074 -0.48718057
#> [3,] 0.08052966 -2.55781074 2.59523899 1.18297439
#> [4,] 0.04831003 -0.48718057 1.18297439 1.01330227
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006638985 -0.005385861 0.005631786 0.002695394
#> [2,] -0.005385861 0.186581188 -0.091295000 -0.013631733
#> [3,] 0.005631786 -0.091295000 0.218880677 0.203588237
#> [4,] 0.002695394 -0.013631733 0.203588237 0.225898401
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006344267 -0.007666977 0.01055004 0.004270121
#> [2,] -0.007666977 0.114026793 -0.08826276 -0.001669227
#> [3,] 0.010550044 -0.088262756 0.33208978 0.321595359
#> [4,] 0.004270121 -0.001669227 0.32159536 0.391583751
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.02008147 -0.1851489 0.2914674 0.1967419
#> [2,] -0.18514892 6.3885016 -4.9706100 -0.8471166
#> [3,] 0.29146737 -4.9706100 7.0819027 4.4310557
#> [4,] 0.19674186 -0.8471166 4.4310557 4.5551441
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.009638317 -0.0084111206 0.06121735 0.0555376002
#> [2,] -0.008411121 0.1579487639 -0.12316044 -0.0008352712
#> [3,] 0.061217353 -0.1231604399 0.69419435 0.6073412622
#> [4,] 0.055537600 -0.0008352712 0.60734126 0.6170863051
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006740939 -0.06169364 0.04506303 0.01053986
#> [2,] -0.061693638 3.50160482 -2.95212446 -0.92597544
#> [3,] 0.045063034 -2.95212446 3.34917047 1.76533284
#> [4,] 0.010539862 -0.92597544 1.76533284 1.37420611
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006159821 -0.00625922 0.004297206 -0.00102371
#> [2,] -0.006259220 0.12439547 -0.071979757 -0.01946861
#> [3,] 0.004297206 -0.07197976 0.186862072 0.17160337
#> [4,] -0.001023710 -0.01946861 0.171603373 0.18357788
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.004288103 -0.008610496 0.009965321 0.004018691
#> [2,] -0.008610496 0.214639915 -0.183774254 -0.023146868
#> [3,] 0.009965321 -0.183774254 0.414739284 0.334128576
#> [4,] 0.004018691 -0.023146868 0.334128576 0.387919695
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.01553577 -0.1391626 0.169296 0.08539981
#> [2,] -0.13916257 9.4652977 -6.244819 0.04512190
#> [3,] 0.16929602 -6.2448186 5.931170 2.14348425
#> [4,] 0.08539981 0.0451219 2.143484 2.63426724
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.006296538 -0.02160850 0.04851166 0.03254773
#> [2,] -0.021608499 0.26717930 -0.30207414 -0.09453187
#> [3,] 0.048511658 -0.30207414 0.66956963 0.44457162
#> [4,] 0.032547725 -0.09453187 0.44457162 0.38266109
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.009124972 -0.09119968 0.05714088 0.004008237
#> [2,] -0.091199678 2.85233472 -2.16959606 -0.496387363
#> [3,] 0.057140882 -2.16959606 2.34110791 1.166817501
#> [4,] 0.004008237 -0.49638736 1.16681750 0.991294080
#>
#>
#> $A_c
#> , , 1, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9237584 0.3176184 -0.2939912 -0.1052225
#> [2,] -0.3767617 -0.2653304 2.6038140 2.8418388
#> [3,] -0.9015574 -2.9796740 7.2364553 6.7680106
#> [4,] 0.8095701 2.6970454 -5.5090447 -4.9291441
#> [5,] 5.7784923 5.1825879 -24.8282765 -34.1370920
#>
#> , , 2, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9158771 0.0688558 -0.3028265 -0.3347265
#> [2,] -0.3527865 0.5261305 0.4874389 0.9125092
#> [3,] -0.2387234 -0.5612327 1.1811499 0.9339116
#> [4,] 0.2612423 0.5433607 -0.6000636 -0.2399614
#> [5,] 3.1531164 0.2784740 33.9624026 28.5039256
#>
#> , , 3, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6291251 -4.914519 4.243588 1.25158031
#> [2,] -0.4035496 2.494532 -1.720192 -0.14762554
#> [3,] -0.6220316 3.978023 -2.617441 -0.04363269
#> [4,] 0.4897016 -3.307937 3.066271 1.10146635
#> [5,] 16.9259135 86.517843 -71.623089 -30.52116506
#>
#> , , 4, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8789507 0.1186262 0.3747961 0.3480881
#> [2,] -0.1710843 -1.5910463 0.2609468 -0.1997769
#> [3,] -0.2230117 -2.6599020 1.1929236 0.1470277
#> [4,] 0.1981026 2.7522891 -0.4134238 0.7531385
#> [5,] 5.1706481 -8.8175430 6.9005135 -0.6349374
#>
#> , , 5, 1
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6226406 -4.082291 1.556776 -1.321828
#> [2,] 0.8993752 -1.539946 3.035408 2.179109
#> [3,] 1.4732627 -3.567699 5.584855 3.543018
#> [4,] -1.3284410 3.578511 -4.879894 -2.808123
#> [5,] 1.3608066 112.382247 -25.873828 51.694264
#>
#> , , 1, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.8614715 0.2626392 0.2676366 0.4751594
#> [2,] -0.3537642 0.6297165 1.9186270 2.6196328
#> [3,] -0.7743063 -1.0670679 6.4299276 6.9592823
#> [4,] 0.6777589 0.9933366 -5.0016384 -5.3189772
#> [5,] 7.6882994 -3.4643615 -21.3760477 -35.8606726
#>
#> , , 2, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0325460 0.01608323 -0.1468528 -0.1979904
#> [2,] -0.4242670 0.81474246 1.7916788 2.7162127
#> [3,] -0.4900834 -0.22216629 3.3722032 3.6174606
#> [4,] 0.4710888 0.18032115 -2.4332042 -2.5975649
#> [5,] 1.4932423 2.99285012 8.9469414 4.5049477
#>
#> , , 3, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5330506 -3.272549 -1.291501 -4.123121
#> [2,] -0.3946698 3.684049 -4.766586 -2.973232
#> [3,] -0.5758675 5.073393 -6.484917 -3.999611
#> [4,] 0.4515851 -4.079116 5.883148 4.037076
#> [5,] 18.9190220 20.381155 130.125415 160.906291
#>
#> , , 4, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9556238 -0.3727344 1.413626 1.072129
#> [2,] -1.0261340 1.0620586 -6.806836 -6.267221
#> [3,] -1.4571007 0.5273199 -8.356807 -8.308879
#> [4,] 1.3823277 -0.4040667 8.453167 8.526058
#> [5,] 6.6850003 1.1454481 31.376791 31.714815
#>
#> , , 5, 2
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.7021634 -1.5784874 -0.6669451 -1.807955
#> [2,] 0.4220162 1.3978674 0.4954964 1.531078
#> [3,] 0.6896587 1.1020025 1.4979543 2.464489
#> [4,] -0.6727623 -0.5867234 -1.1117581 -1.678504
#> [5,] 6.9866223 14.4496763 52.9516987 61.296088
#>
#> , , 1, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9792232 0.3184536 0.0751472 0.2451399
#> [2,] -0.4397268 0.7265166 1.9636890 2.7408957
#> [3,] -0.8998612 -0.8684513 6.6909166 7.3556161
#> [4,] 0.7813072 0.8491214 -5.2582243 -5.6810414
#> [5,] 6.2423525 -7.3164988 -16.3894485 -31.5205122
#>
#> , , 2, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.0279137 -0.01654963 -0.4779219 -0.6295964
#> [2,] -0.3611918 1.09500893 2.3232906 3.6621966
#> [3,] -0.4496924 0.20029141 3.7958865 4.5990678
#> [4,] 0.4346754 -0.10346066 -2.8209907 -3.3860821
#> [5,] 0.7455035 -6.07039349 10.6937962 -3.1347565
#>
#> , , 3, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.4636506 -1.801681 -2.836163 -4.696384
#> [2,] -0.3280844 2.790617 -3.241187 -2.032857
#> [3,] -0.4704671 3.760300 -4.202837 -2.569727
#> [4,] 0.3628199 -2.772291 3.783628 2.770519
#> [5,] 19.4537543 -10.285828 151.394606 162.875611
#>
#> , , 4, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.179742 -0.4173993 3.293661 2.938007
#> [2,] -1.343586 1.0883394 -7.219364 -6.729363
#> [3,] -1.729283 0.5216087 -8.848088 -8.874844
#> [4,] 1.606101 -0.3704069 8.545702 8.711873
#> [5,] 4.767281 0.1486965 12.447307 11.740486
#>
#> , , 5, 3
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5752603 -1.5907246 -0.4740389 -1.567716
#> [2,] 0.4956433 0.5137182 1.4820744 2.033484
#> [3,] 0.8435393 -0.5651861 3.3151206 3.363491
#> [4,] -0.7815763 0.7905446 -2.6304594 -2.447847
#> [5,] 7.8268359 30.5508457 31.2980057 47.590140
#>
#> , , 1, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9127343 0.34817766 0.04105692 0.2480794
#> [2,] -0.3429016 1.15172738 1.56804229 2.4893301
#> [3,] -0.7136697 -0.06248393 6.10765813 7.0933477
#> [4,] 0.6254964 0.23140656 -4.83851424 -5.5104626
#> [5,] 6.2657096 -17.05473509 -7.04087116 -26.2853752
#>
#> , , 2, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9871157 0.1510725 -0.6251528 -0.6427566
#> [2,] -0.5953566 1.4376976 1.9895721 3.5955897
#> [3,] -0.7664256 0.2649324 3.4280778 4.2731111
#> [4,] 0.6605776 -0.1650494 -2.5152888 -3.1131839
#> [5,] 8.5980158 -15.3559360 20.0301497 -1.7230947
#>
#> , , 3, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.4289024 -0.8777867 -3.887324 -5.239835
#> [2,] -0.2031791 5.4444554 -5.392542 -2.449287
#> [3,] -0.2915534 7.9614705 -7.636085 -3.267482
#> [4,] 0.2036748 -6.2337543 6.669366 3.419903
#> [5,] 18.7802895 -78.1892975 209.622566 177.862250
#>
#> , , 4, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 1.214141 -0.1246835 2.497895 2.419087
#> [2,] -1.405887 1.8768968 -8.948952 -7.773100
#> [3,] -1.829754 1.6563730 -10.490582 -9.560965
#> [4,] 1.703335 -1.6124041 10.382550 9.496140
#> [5,] 4.131545 0.8947960 19.756667 19.287365
#>
#> , , 5, 4
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6324871 -3.084416 1.159065 -0.828074
#> [2,] 0.6289834 -2.265936 3.879989 2.695991
#> [3,] 1.0501752 -4.838602 6.919291 4.277333
#> [4,] -0.9595624 4.543299 -5.920100 -3.392209
#> [5,] 4.5224470 104.324303 -34.184713 28.151397
#>
#> , , 1, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9522642 0.1770790 -0.09125172 0.008262259
#> [2,] -0.2247011 0.6715038 2.03970653 2.719489038
#> [3,] -0.5462980 -0.6939181 6.38216483 7.026897081
#> [4,] 0.4947780 0.5801095 -4.91874594 -5.392550162
#> [5,] 3.3050605 1.3066515 -15.88818456 -25.423203426
#>
#> , , 2, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9819213 -0.1150641 -0.8447847 -1.134314
#> [2,] -0.5909728 1.1544736 1.7297671 3.036099
#> [3,] -0.7541999 0.2805735 3.1828032 3.978170
#> [4,] 0.6601384 -0.2052592 -2.3677926 -2.961599
#> [5,] 7.8942603 -2.0368546 34.0926905 26.855664
#>
#> , , 3, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.5776031 -3.787185 -0.1822904 -3.1347230
#> [2,] -0.1640935 4.628507 -3.3394918 -0.6615546
#> [3,] -0.2035787 6.457345 -4.1930304 -0.3743366
#> [4,] 0.1559125 -5.214935 4.0864452 1.1566031
#> [5,] 13.1714003 16.624005 73.2293534 91.2045495
#>
#> , , 4, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.9141649 -0.1155163 0.9922254 0.9291438
#> [2,] -0.5362622 3.5509821 -4.4357347 -1.8871572
#> [3,] -0.7994902 3.7723770 -5.1718385 -2.5024475
#> [4,] 0.7606672 -3.5632548 5.5809767 3.0840651
#> [5,] 5.0886435 -12.3030433 18.7034085 7.6869207
#>
#> , , 5, 5
#>
#> [,1] [,2] [,3] [,4]
#> [1,] 0.6447673 -3.574139 1.6549380 -0.5464694
#> [2,] 0.5844216 1.782771 -0.9073542 0.1720491
#> [3,] 0.9717333 1.909274 -0.9722594 0.1728653
#> [4,] -0.8851301 -1.350673 1.0410202 0.2801143
#> [5,] 4.3897196 66.167434 9.0374869 47.2797816
#>
#>
## ------------------------------------------------
## Method `PosteriorBVARPANEL$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
#> **************************************************|