An Application to HB Twofold Normal Model On sampel dataset

library(saeHB.twofold)
data("dataTwofold")

model=NormalTF(y~x1+x2,vardir="vardir",area = "codearea",weight = "w",iter.mcmc = 100000,thin=50,burn.in = 1000,data=dataTwofold)
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 90
#>    Unobserved stochastic nodes: 125
#>    Total graph size: 953
#> 
#> Initializing model
#> 
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 90
#>    Unobserved stochastic nodes: 125
#>    Total graph size: 953
#> 
#> Initializing model
#> 
#> Compiling model graph
#>    Resolving undeclared variables
#>    Allocating nodes
#> Graph information:
#>    Observed stochastic nodes: 90
#>    Unobserved stochastic nodes: 125
#>    Total graph size: 953
#> 
#> Initializing model
#> Warning in par(opar): argument 1 does not name a graphical parameter

CV=(model$Est_sub$SD)/(model$Est_sub$Mean)*100
MSE=model$Est_sub$SD^2
summary(cbind(CV,MSE))
#>        CV              MSE         
#>  Min.   : 3.124   Min.   : 0.2246  
#>  1st Qu.: 6.587   1st Qu.: 0.6957  
#>  Median :11.508   Median : 1.6950  
#>  Mean   :13.763   Mean   : 2.3983  
#>  3rd Qu.:17.285   3rd Qu.: 3.4049  
#>  Max.   :50.365   Max.   :11.5196

CV2=(model$Est_area$SD)/(model$Est_area$Mean)*100
MSE2=model$Est_area$SD^2
summary(cbind(CV2,MSE2))
#>       CV2              MSE2       
#>  Min.   : 3.641   Min.   :0.1562  
#>  1st Qu.: 5.168   1st Qu.:0.4531  
#>  Median : 7.461   Median :0.6850  
#>  Mean   : 8.643   Mean   :1.0243  
#>  3rd Qu.:11.796   3rd Qu.:1.2855  
#>  Max.   :19.813   Max.   :3.7562

dirCV=sqrt(dataTwofold$vardir)/(dataTwofold$y)*100
summary(cbind(dirCV,CV))
#>      dirCV               CV        
#>  Min.   :  3.187   Min.   : 3.124  
#>  1st Qu.:  6.642   1st Qu.: 6.587  
#>  Median : 12.763   Median :11.508  
#>  Mean   : 25.141   Mean   :13.763  
#>  3rd Qu.: 21.041   3rd Qu.:17.285  
#>  Max.   :680.378   Max.   :50.365

boxplot(cbind(dirCV,CV),ylim=c(0,50))

model$refVar
#>   var_area  var_sub
#> 1 8.085016 8.828761

model$plot
#> [[1]]
#> NULL
#> 
#> [[2]]
#> [[2]]$mar
#> [1] 5.1 4.1 4.1 2.1
#> 
#> 
#> [[3]]
#> [[1]]
#> Markov Chain Monte Carlo (MCMC) output:
#> Start = 1050 
#> End = 1e+05 
#> Thinning interval = 50 
#>              beta[0]       beta[1]  beta[2]
#>    [1,]  0.241624462  0.4476526287 1.245501
#>    [2,] -0.128314720  0.1193991458 1.188790
#>    [3,]  0.485335153 -0.6795958908 1.196801
#>    [4,]  0.138013320  0.4904752957 1.093812
#>    [5,] -0.479717971 -0.0956399574 1.225508
#>    [6,]  0.361640603  0.0518144981 1.153586
#>    [7,] -0.878749522  0.6519765774 1.265095
#>    [8,] -0.222329174 -0.0176393960 1.276749
#>    [9,]  0.143053164  0.2847920908 1.162858
#>   [10,] -1.788429061 -0.3930318479 1.317838
#>   [11,] -1.274343427 -0.2728579088 1.306119
#>   [12,] -0.515083651  1.0791580368 1.280770
#>   [13,]  0.818654701 -0.4777767060 1.141289
#>   [14,] -0.103411605  0.4231381229 1.112074
#>   [15,] -0.859878260  0.4467432660 1.255256
#>   [16,] -0.318764780  0.7320868769 1.265033
#>   [17,]  0.292926397  0.0844303063 1.131794
#>   [18,]  0.317818607  0.5105131133 1.213762
#>   [19,]  0.508631043  0.5935940566 1.080929
#>   [20,] -0.012720913 -0.4024671385 1.222869
#>   [21,] -1.460529330 -0.1863605480 1.269223
#>   [22,] -1.170666002  0.2989098092 1.367505
#>   [23,]  0.038941093  0.7195166700 1.076106
#>   [24,] -0.540593800  0.1878627426 1.322064
#>   [25,] -1.425422631  0.2668612964 1.328410
#>   [26,]  0.477582882  0.6274042575 1.188882
#>   [27,] -0.812790548  0.7273256273 1.249465
#>   [28,]  0.785627876 -0.0908253123 1.133339
#>   [29,] -0.360439733 -0.1534124386 1.239602
#>   [30,] -0.112612052 -0.5394550435 1.221169
#>   [31,] -1.435117696  0.3978285633 1.253403
#>   [32,] -0.386538123  0.7793180870 1.256431
#>   [33,]  0.150709842  1.3101910217 1.191338
#>   [34,] -0.473289586  0.3159666421 1.135797
#>   [35,] -0.573302315  0.1039267443 1.262889
#>   [36,]  0.654425592 -0.5573534048 1.196653
#>   [37,] -0.852095308  0.8759173798 1.286564
#>   [38,]  0.314644064  0.1205912407 1.103865
#>   [39,]  0.506829998  0.8956045766 1.037447
#>   [40,] -0.486503595  0.7998110006 1.270106
#>   [41,] -0.048445353 -0.0543715909 1.196340
#>   [42,] -0.181898737  0.4587462820 1.266197
#>   [43,] -1.378875737 -0.1610297013 1.189976
#>   [44,]  0.004959343 -1.2817151377 1.318174
#>   [45,] -0.782274772  0.5201446464 1.116090
#>   [46,]  0.712539281 -0.7143993353 1.272377
#>   [47,] -1.048998875  0.2815751342 1.227156
#>   [48,]  0.659314112  0.5777078986 1.148761
#>   [49,] -0.074699783  0.3484107183 1.199449
#>   [50,] -0.652723063 -0.0673897272 1.151401
#>   [51,]  0.107685671  0.4301231987 1.268063
#>   [52,] -0.849111371  1.0737962895 1.265589
#>   [53,] -0.598776579  0.8244702607 1.298662
#>   [54,] -0.049972239  0.6630108092 1.137442
#>   [55,] -0.661133238 -0.3117812236 1.330852
#>   [56,] -0.653531002  0.6478735985 1.228323
#>   [57,] -1.050126521 -0.5053069158 1.284421
#>   [58,] -0.953010115  0.4928977842 1.367012
#>   [59,]  0.199872663 -0.0715748436 1.117223
#>   [60,]  0.498801494  1.3236328941 1.125753
#>   [61,] -0.472552228  0.3488034302 1.181987
#>   [62,] -1.481761118  0.3806689504 1.367238
#>   [63,] -0.158436054  0.2945986656 1.242346
#>   [64,]  0.246099802  0.0342972459 1.199554
#>   [65,] -1.331181891 -0.4685070461 1.304795
#>   [66,]  0.784279889  0.4062513874 1.187298
#>   [67,] -0.150782627 -0.9863847412 1.243143
#>   [68,] -0.097072522  1.1081364455 1.142919
#>   [69,]  0.067982156  0.2145817266 1.156745
#>   [70,] -0.034721416  0.9664894986 1.139418
#>   [71,]  0.237843825  0.6921780215 1.154977
#>   [72,] -0.356429173  0.3083989841 1.245339
#>   [73,] -0.202322620 -0.1615858442 1.201793
#>   [74,] -0.232099905 -0.7976405025 1.248575
#>   [75,] -1.364322001  0.2968666160 1.353994
#>   [76,] -0.741982376  0.6722162383 1.202483
#>   [77,] -0.205747200 -0.1999915753 1.272986
#>   [78,] -0.287123716 -0.2845862113 1.239419
#>   [79,] -1.010037647  1.0325177793 1.201612
#>   [80,] -0.815846106  0.0088826295 1.316861
#>   [81,]  0.119713860  0.4795707026 1.187095
#>   [82,]  0.504530700  0.6640396233 1.172791
#>   [83,] -0.682153080  0.7579294622 1.145487
#>   [84,] -0.910422301  0.4661837422 1.283324
#>   [85,] -0.497813175  1.7489475517 1.047087
#>   [86,] -0.909787890  0.2724900629 1.278363
#>   [87,] -0.228621438  0.2919482995 1.273005
#>   [88,] -0.434641451  0.5642400413 1.136370
#>   [89,] -0.199132217  0.0864417383 1.188381
#>   [90,] -0.964748552  0.3035407883 1.292012
#>   [91,] -0.283578025 -0.0430051510 1.219086
#>   [92,]  0.405158817 -0.5700219055 1.313604
#>   [93,] -1.549152388  0.8497195624 1.224732
#>   [94,] -0.712859229 -0.7285915032 1.394173
#>   [95,] -0.925020646 -0.1324596830 1.344713
#>   [96,] -0.888982209  1.1601512412 1.278624
#>   [97,] -1.413059876  0.3855453743 1.318328
#>   [98,] -1.143353962  0.6793571987 1.261162
#>   [99,] -1.175594321  0.7775760512 1.288046
#>  [100,] -0.152513633  0.2705464519 1.172651
#>  [101,] -1.162669571 -0.0283721769 1.365088
#>  [102,]  0.464031340  0.0464962078 1.108230
#>  [103,] -1.246869589  1.3044079155 1.267636
#>  [104,]  0.250305135  0.6110599912 1.158385
#>  [105,] -0.336911140  0.1426678248 1.251140
#>  [106,] -0.119176817 -0.0669685078 1.237545
#>  [107,] -0.614800617 -0.1668123122 1.239491
#>  [108,] -0.686244043  0.6234667979 1.259548
#>  [109,] -0.066576766  0.5763578677 1.234033
#>  [110,]  0.586481754  1.2700270041 1.121986
#>  [111,] -0.013015275 -0.0005558398 1.164495
#>  [112,]  0.870620067 -0.7788035553 1.145499
#>  [113,] -2.783326654  0.3349469247 1.276183
#>  [114,] -0.543261419  0.7796182198 1.290726
#>  [115,] -0.193196784 -0.3904045789 1.199354
#>  [116,] -0.224200129  0.5688933390 1.273701
#>  [117,] -0.601636037  0.1623495521 1.275953
#>  [118,]  0.080025483  0.0444848561 1.168489
#>  [119,]  0.328793916  0.5622730860 1.191879
#>  [120,]  0.048305329 -0.5861346637 1.232074
#>  [121,] -0.331711541  0.2879197014 1.294272
#>  [122,]  0.180760854 -0.5758907606 1.201040
#>  [123,] -0.383750658  0.0234355417 1.275715
#>  [124,] -0.710549832  0.4434045143 1.273320
#>  [125,] -0.193768400  0.6081856301 1.144048
#>  [126,] -0.086690086 -0.2103772367 1.191821
#>  [127,] -0.266927397  0.3288662207 1.161379
#>  [128,] -0.706039061  0.1695990092 1.240400
#>  [129,] -0.104978067  0.2248324053 1.237481
#>  [130,] -0.060811464  0.7263841574 1.211422
#>  [131,]  0.090558343  0.0674739607 1.187549
#>  [132,] -0.596939661 -0.7898638887 1.254196
#>  [133,] -0.382772221  0.1430192601 1.276544
#>  [134,]  0.631577826  0.6918112888 1.208386
#>  [135,] -0.168751844  0.0809628105 1.136824
#>  [136,] -0.550014244  0.3546577763 1.189952
#>  [137,] -0.200506222 -0.0646277862 1.356919
#>  [138,] -0.394871425  0.0636535252 1.288876
#>  [139,] -0.517346805  1.5122619580 1.174121
#>  [140,] -0.174961828  0.1169677204 1.257857
#>  [141,]  0.120779984 -0.8815732288 1.239201
#>  [142,] -0.117464266 -1.4266824114 1.333952
#>  [143,] -1.032359144  0.5930712978 1.257364
#>  [144,] -0.026374398  0.8098133270 1.236617
#>  [145,]  0.137553492 -0.0327826227 1.169674
#>  [146,] -0.200237074  0.2296874554 1.086283
#>  [147,] -0.493094974  0.4121762626 1.176400
#>  [148,] -1.045945468  0.0735793063 1.246091
#>  [149,] -0.586528464  0.6489601743 1.281455
#>  [150,] -0.360843171 -1.1424518860 1.266257
#>  [151,] -0.192826748  0.2433370354 1.269777
#>  [152,] -0.352610817  0.1592586164 1.276704
#>  [153,] -0.560961824 -0.6429747488 1.269501
#>  [154,]  0.518031091 -1.5118376450 1.147470
#>  [155,] -1.301400249  0.8823804561 1.220571
#>  [156,] -0.319370142  1.0521771996 1.167475
#>  [157,]  0.292658677  0.0870734390 1.269832
#>  [158,] -0.046189620 -0.3035735149 1.218207
#>  [159,] -0.219112926 -0.1670583125 1.227966
#>  [160,] -0.880672260 -0.0890235085 1.240555
#>  [161,] -0.336749898  0.5387938268 1.163280
#>  [162,] -1.080288257  0.8788642422 1.328150
#>  [163,] -1.448943604  0.1976926783 1.235006
#>  [164,] -1.216301806  1.1718992583 1.321352
#>  [165,] -2.271947636 -0.6508251719 1.414008
#>  [166,] -0.975155761  0.8486608341 1.171028
#>  [167,] -0.397429115 -0.7692988247 1.197414
#>  [168,] -0.180611038  0.5766437259 1.195009
#>  [169,] -0.693659277  1.0265216975 1.153692
#>  [170,] -0.678454147  0.3260915422 1.200264
#>  [171,] -1.478092605 -0.1144670764 1.348160
#>  [172,]  0.162941537 -0.4208937491 1.285300
#>  [173,]  0.375015543 -0.6420090289 1.183279
#>  [174,] -0.945965205 -0.3219655705 1.312963
#>  [175,] -0.850931261  0.5767563192 1.264107
#>  [176,] -0.477126027 -0.2092679724 1.265045
#>  [177,] -0.937663409  0.8413991088 1.169911
#>  [178,] -0.789262947  0.1085608771 1.212605
#>  [179,] -0.312667456  0.9745172710 1.218518
#>  [180,]  0.489083408 -0.0780436794 1.222116
#>  [181,] -0.760326002 -0.0125399647 1.220160
#>  [182,] -0.265532735  0.3881476932 1.152842
#>  [183,]  0.963942512  0.3987538116 1.142456
#>  [184,] -0.813616572 -0.2142570546 1.233687
#>  [185,] -0.251470856  0.1210855593 1.185082
#>  [186,]  0.370983613 -0.5042196654 1.271550
#>  [187,] -0.455879433  1.4308348268 1.186146
#>  [188,] -0.215120405 -0.1304627727 1.237823
#>  [189,] -1.367360357  0.2172901955 1.326088
#>  [190,]  0.254799069  0.0330077899 1.235977
#>  [191,] -0.122377334 -0.4664411615 1.107757
#>  [192,]  0.769138507 -1.0645213225 1.267810
#>  [193,]  0.580629196 -0.0078237769 1.239676
#>  [194,] -0.039990927 -0.7965822182 1.140496
#>  [195,] -1.245235686  0.7770641251 1.180436
#>  [196,] -0.308245725 -0.3177207051 1.185261
#>  [197,] -0.545307945  0.6038536740 1.293314
#>  [198,] -2.299598927  1.1654602073 1.374016
#>  [199,] -0.465979475 -0.3055801769 1.297330
#>  [200,] -0.176573743  0.6925366841 1.310214
#>  [201,] -0.456516405  0.0285125438 1.260527
#>  [202,] -1.124917426  0.9392267506 1.234759
#>  [203,] -0.190882792  1.4445003930 1.253042
#>  [204,]  0.312451437  0.6502459023 1.169663
#>  [205,]  1.456111664 -0.1749230616 1.136057
#>  [206,] -1.786702802  0.5537932952 1.327595
#>  [207,] -1.407834515 -0.0935328011 1.319089
#>  [208,] -1.055083170  0.9196968185 1.208630
#>  [209,] -0.158556032  0.7064432605 1.237288
#>  [210,] -0.416803440 -0.4428801092 1.314197
#>  [211,] -0.200905360  0.1537026497 1.197136
#>  [212,]  0.313552882  1.1614854950 1.207320
#>  [213,]  0.581616959 -0.3882022299 1.251855
#>  [214,]  0.547863228  0.2393022265 1.186085
#>  [215,] -0.163887926  0.0756116344 1.252073
#>  [216,] -0.078959261  0.1748895145 1.223102
#>  [217,]  0.301227284 -0.3319054652 1.212337
#>  [218,] -0.346497841  0.5465404703 1.235192
#>  [219,] -0.942649680 -0.1495152369 1.259341
#>  [220,] -0.262536649 -0.6887962835 1.246916
#>  [221,] -1.222597575  0.4426408596 1.284777
#>  [222,] -1.370283402  1.3086133859 1.292204
#>  [223,] -0.465245985  0.6885631736 1.210651
#>  [224,] -0.186025291  0.8604809867 1.236324
#>  [225,]  0.243142084 -0.5975198068 1.203005
#>  [226,]  0.052350763 -0.8794828693 1.244463
#>  [227,]  0.180095929 -0.5143184046 1.243654
#>  [228,] -0.741396507  1.3619858558 1.240573
#>  [229,]  0.506001993  0.6419758697 1.212458
#>  [230,] -0.801460516 -0.0211446389 1.253820
#>  [231,] -0.707037085  0.6563184715 1.240962
#>  [232,] -0.398333632  0.2638202572 1.120064
#>  [233,] -1.329950168 -0.4837653025 1.333961
#>  [234,] -0.298883859  0.6693368162 1.255932
#>  [235,] -1.447466865  1.2600074336 1.276242
#>  [236,]  0.107919887 -0.8626073128 1.194422
#>  [237,] -1.385467147 -0.1884148460 1.243052
#>  [238,] -0.103188362 -0.1281201935 1.228004
#>  [239,] -0.362910741  0.0871800858 1.314955
#>  [240,] -1.064423984  0.2231038406 1.306090
#>  [241,] -0.436221692  0.7366607032 1.167995
#>  [242,] -0.328574475  0.1647152765 1.222536
#>  [243,] -0.159774700  0.5422673330 1.158360
#>  [244,]  1.172801067 -0.7898686547 1.155749
#>  [245,]  0.471166802 -0.3630630047 1.176774
#>  [246,]  0.600686231 -0.0647975050 1.065322
#>  [247,]  0.142575566  0.1112198554 1.148391
#>  [248,] -0.758256353  0.3082198603 1.216240
#>  [249,] -1.013619006  1.3912931262 1.173385
#>  [250,] -0.248146045 -0.0245796493 1.217561
#>  [251,] -1.190330484 -0.3699240535 1.307229
#>  [252,] -0.975753544  0.6335051357 1.238118
#>  [253,] -0.542702426  0.2393952168 1.140601
#>  [254,] -0.564384951 -0.0605505293 1.213498
#>  [255,]  0.248710281  0.9874720405 1.168666
#>  [256,]  0.301990826 -0.8923799197 1.234290
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#> [1896,] -0.175590908  0.0530166572 1.218491
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#> [1898,]  0.798815555  0.7596602367 1.128104
#> [1899,] -0.005280227 -0.6666653339 1.243538
#> [1900,] -0.279687986  0.1285281625 1.147984
#> [1901,] -0.846338763 -0.4512672850 1.292847
#> [1902,] -0.185670116  0.4314044681 1.117884
#> [1903,]  0.549438566  0.3930381759 1.149250
#> [1904,]  0.423162549 -0.0286202460 1.082243
#> [1905,] -1.164393836 -0.3335810752 1.302235
#> [1906,] -1.526512484 -0.5828485523 1.302773
#> [1907,] -0.452297039 -0.1013732682 1.268739
#> [1908,] -0.565416882  1.3261541037 1.265630
#> [1909,]  0.906613140 -0.2762251756 1.108005
#> [1910,] -0.189607705  0.2094408854 1.310653
#> [1911,]  1.161586725 -0.1640683807 1.110691
#> [1912,] -0.950429503  0.1652136123 1.240496
#> [1913,] -1.063526198  0.6478517712 1.291682
#> [1914,] -0.905240495  1.0057012769 1.253860
#> [1915,] -0.795043750  0.4902773106 1.189918
#> [1916,] -1.236555215  0.0571018263 1.314405
#> [1917,] -1.014930485  0.4740259948 1.258815
#> [1918,]  0.311749101  0.6497128323 1.204879
#> [1919,] -1.487626549  0.0421672358 1.217034
#> [1920,]  0.002211793  1.0855294778 1.266816
#> [1921,]  0.581449587 -0.0773631033 1.183290
#> [1922,] -1.539320577  0.4437939645 1.226656
#> [1923,] -0.476058080  0.9843682123 1.176719
#> [1924,] -1.330361688  1.0804314819 1.312819
#> [1925,] -0.539205176 -0.3299354747 1.253914
#> [1926,] -1.076437692  0.6755113299 1.260128
#> [1927,] -0.573417879  1.0658383541 1.248252
#> [1928,]  0.302786078 -0.6734516229 1.238573
#> [1929,]  0.142244567  0.3544276109 1.196238
#> [1930,] -0.577711700 -0.9776208538 1.335830
#> [1931,]  0.520929077  0.1089413015 1.143424
#> [1932,]  1.101857163  0.5517745105 1.134464
#> [1933,] -0.444733149 -0.2983245921 1.164609
#> [1934,] -0.179213747 -0.1360913928 1.255179
#> [1935,] -0.639760175  0.4445310029 1.220200
#> [1936,] -0.781240572  0.6439369422 1.268260
#> [1937,] -0.761179164  1.2579494563 1.193746
#> [1938,]  0.632275804  1.2760722030 1.100951
#> [1939,]  0.095911025  0.0946747132 1.161074
#> [1940,] -0.827104019  1.0379555712 1.280372
#> [1941,]  0.065725306  1.0823562841 1.085266
#> [1942,] -0.714870200  0.5087587748 1.155961
#> [1943,] -0.163775606  0.9304403777 1.284346
#> [1944,]  0.319233789  0.9964698703 1.082057
#> [1945,] -0.148489084 -0.2276626817 1.210291
#> [1946,] -0.839697567  0.9543235364 1.269875
#> [1947,] -0.599460807 -0.1240313381 1.304764
#> [1948,] -0.106361368 -0.3427565083 1.207435
#> [1949,] -0.089441289 -1.6221007407 1.268120
#> [1950,] -0.669283692  0.3991254056 1.356604
#> [1951,] -0.147258483  0.1451616134 1.231238
#> [1952,]  0.881760871 -0.2520864534 1.228431
#> [1953,] -0.775232407  0.3410157268 1.226946
#> [1954,] -1.093729797  0.6412482828 1.339187
#> [1955,] -0.495388951 -0.7579623822 1.360708
#> [1956,]  0.316246169 -0.0999225144 1.159388
#> [1957,] -1.022739095  1.0552113749 1.179245
#> [1958,] -0.741114027  0.3384964668 1.141942
#> [1959,]  0.149209879 -0.2676532954 1.181896
#> [1960,]  0.991151338  0.1252573622 1.119790
#> [1961,]  0.462334806 -0.1695818683 1.074099
#> [1962,] -0.966202137  0.7208790336 1.306727
#> [1963,] -1.386343511  1.2217933813 1.302450
#> [1964,] -1.038535446  0.9952072491 1.232174
#> [1965,] -0.514888570 -0.2254197000 1.249179
#> [1966,] -0.400596793 -0.0414112866 1.170659
#> [1967,]  0.026489495  0.1026858834 1.132198
#> [1968,]  0.561993430  0.1617227818 1.173025
#> [1969,] -0.550694337  0.4537593596 1.206836
#> [1970,] -0.207986225  0.2005757710 1.213271
#> [1971,] -0.986185792  1.0195656442 1.197716
#> [1972,] -0.471913756 -0.0355703287 1.285234
#> [1973,] -0.705372604  0.3809798790 1.241107
#> [1974,] -0.659110913  0.0508985085 1.220782
#> [1975,] -0.608377821 -0.2067524012 1.226081
#> [1976,]  0.125024104 -0.3302995765 1.224594
#> [1977,] -0.093024126 -0.7939716790 1.213668
#> [1978,] -1.170163433  0.6339202340 1.295023
#> [1979,] -0.618509350  0.3911386917 1.187980
#> [1980,]  0.749955628 -0.0860244039 1.178732
#> 
#> attr(,"class")
#> [1] "mcmc.list"
#> 
#> [[4]]
#> NULL