Highest Posterior Density intervals for objects of class mtar
Source: R/bayesians.R
HPDinterval.mtar.RdHighest Posterior Density intervals for objects of class mtar
Arguments
- obj
an object of class
mtargenerated by a call to the functionmtar().- prob
a numeric scalar in the interval \((0,1)\) giving the target probability content of the intervals. By default,
probis set to0.95.- ...
Optional additional arguments for methods. None are used at present.
Examples
# \donttest{
###### Example 1: Returns of the closing prices of three financial indexes
data(returns)
fit1 <- mtar(~ COLCAP + BOVESPA | SP500, data=returns, row.names=Date,
subset={Date<="2015-12-07"}, dist="Student-t",
ars=ars(nregim=3,p=c(1,1,2)), n.burnin=100, n.sim=200,
n.thin=2, ssvs=TRUE)
coda::HPDinterval(fit1)
#>
#> Probability = 0.95
#>
#> Thresholds:
#> lower upper
#> Threshold.1 -0.0016244 -0.0012438
#> Threshold.2 0.0045418 0.0046668
#>
#>
#> Autoregressive coefficients:
#> Regime 1:lower Regime 1:upper Regime 2:lower
#> COLCAP:(Intercept) -0.0038301 -0.0022509 -0.00038381
#> COLCAP:COLCAP.lag(1) 0.0428114 0.2431400 -0.00930639
#> COLCAP:COLCAP.lag(2)
#> COLCAP:BOVESPA.lag(1) 0.0140646 0.1328157 0.03708749
#> COLCAP:BOVESPA.lag(2)
#> BOVESPA:(Intercept) -0.0085679 -0.0064163 -0.00084100
#> BOVESPA:COLCAP.lag(1) -0.0969727 0.1548475 -0.09450420
#> BOVESPA:COLCAP.lag(2)
#> BOVESPA:BOVESPA.lag(1) -0.0756523 0.0817256 -0.08680531
#> BOVESPA:BOVESPA.lag(2)
#> Regime 2:upper Regime 3:lower Regime 3:upper
#> COLCAP:(Intercept) 0.00083243 0.0026245 0.0040569
#> COLCAP:COLCAP.lag(1) 0.14430244 -0.0368875 0.1478033
#> COLCAP:COLCAP.lag(2) -0.0283047 0.1471497
#> COLCAP:BOVESPA.lag(1) 0.13583069 0.0400391 0.1569754
#> COLCAP:BOVESPA.lag(2) -0.1242541 -0.0059647
#> BOVESPA:(Intercept) 0.00096980 0.0069095 0.0092296
#> BOVESPA:COLCAP.lag(1) 0.12767120 0.0419791 0.3428645
#> BOVESPA:COLCAP.lag(2) -0.1528390 0.1258414
#> BOVESPA:BOVESPA.lag(1) 0.04339523 -0.1468148 0.0746957
#> BOVESPA:BOVESPA.lag(2) -0.1939853 -0.0349060
#>
#>
#> Scale parameter:
#> Regime 1:lower Regime 1:upper Regime 2:lower Regime 2:upper
#> COLCAP.COLCAP 5.1682e-05 7.1970e-05 3.3409e-05 4.5744e-05
#> COLCAP.BOVESPA 2.2689e-05 4.3157e-05 5.3769e-06 1.5186e-05
#> BOVESPA.BOVESPA 1.0709e-04 1.4737e-04 6.1744e-05 8.4321e-05
#> Regime 3:lower Regime 3:upper
#> COLCAP.COLCAP 4.2753e-05 5.9508e-05
#> COLCAP.BOVESPA 1.5483e-05 3.3092e-05
#> BOVESPA.BOVESPA 1.0495e-04 1.4555e-04
#>
#>
#> Extra parameter:
#> lower upper
#> nu 4.7391 6.5521
###### Example 2: Rainfall and two river flows in Colombia
data(riverflows)
fit2 <- mtar(~ Bedon + LaPlata | Rainfall, data=riverflows, row.names=Date,
subset={Date<="2009-02-13"}, dist="Laplace",
ars=ars(nregim=3,p=5), n.burnin=100, n.sim=200, n.thin=2)
coda::HPDinterval(fit2)
#>
#> Probability = 0.95
#>
#> Thresholds:
#> lower upper
#> Threshold.1 3.0555 3.4272
#> Threshold.2 10.0114 10.0166
#>
#>
#> Autoregressive coefficients:
#> Regime 1:lower Regime 1:upper Regime 2:lower
#> Bedon:(Intercept) 1.089772 1.4998943 1.3259498
#> Bedon:Bedon.lag(1) 0.482409 0.6441843 0.4774448
#> Bedon:Bedon.lag(2) -0.030082 0.1122147 -0.0268180
#> Bedon:Bedon.lag(3) -0.027407 0.0857252 -0.1532360
#> Bedon:Bedon.lag(4) -0.034059 0.0909020 -0.0143516
#> Bedon:Bedon.lag(5) 0.021448 0.1348567 -0.0642091
#> Bedon:LaPlata.lag(1) 0.020743 0.0714711 -0.0045662
#> Bedon:LaPlata.lag(2) -0.040640 0.0021742 -0.0560527
#> Bedon:LaPlata.lag(3) -0.017216 0.0220017 -0.0346755
#> Bedon:LaPlata.lag(4) -0.031534 0.0038988 -0.0203794
#> Bedon:LaPlata.lag(5) -0.020667 0.0080394 -0.0220366
#> LaPlata:(Intercept) 2.736487 3.9127521 5.3889658
#> LaPlata:Bedon.lag(1) -0.051574 0.3491683 -0.1194771
#> LaPlata:Bedon.lag(2) -0.223885 0.1055845 -0.2117400
#> LaPlata:Bedon.lag(3) -0.131851 0.1840651 -0.2818465
#> LaPlata:Bedon.lag(4) -0.274890 0.0692383 0.0045357
#> LaPlata:Bedon.lag(5) 0.015945 0.2879224 -0.4432197
#> LaPlata:LaPlata.lag(1) 0.545524 0.7049934 0.4540068
#> LaPlata:LaPlata.lag(2) -0.125712 -0.0083714 -0.0504552
#> LaPlata:LaPlata.lag(3) 0.010711 0.1139856 -0.0132595
#> LaPlata:LaPlata.lag(4) -0.044584 0.0629166 -0.1333765
#> LaPlata:LaPlata.lag(5) -0.019370 0.0767111 0.0409557
#> Regime 2:upper Regime 3:lower Regime 3:upper
#> Bedon:(Intercept) 2.964205 4.2351827 7.002973
#> Bedon:Bedon.lag(1) 0.666455 0.3140666 0.616146
#> Bedon:Bedon.lag(2) 0.224160 -0.0496686 0.224077
#> Bedon:Bedon.lag(3) 0.055222 -0.2182411 0.027959
#> Bedon:Bedon.lag(4) 0.181956 -0.1503842 0.139549
#> Bedon:Bedon.lag(5) 0.101258 0.0587178 0.311492
#> Bedon:LaPlata.lag(1) 0.052711 0.0125577 0.075942
#> Bedon:LaPlata.lag(2) 0.015635 -0.0371351 0.027788
#> Bedon:LaPlata.lag(3) 0.022886 -0.0072575 0.069416
#> Bedon:LaPlata.lag(4) 0.041919 -0.0308975 0.049126
#> Bedon:LaPlata.lag(5) 0.032213 -0.0462165 0.017075
#> LaPlata:(Intercept) 9.400490 12.7723355 23.578433
#> LaPlata:Bedon.lag(1) 0.303983 0.1307592 1.006624
#> LaPlata:Bedon.lag(2) 0.264843 -0.9859781 -0.019594
#> LaPlata:Bedon.lag(3) 0.149880 -1.0160003 0.060029
#> LaPlata:Bedon.lag(4) 0.428757 -0.6210323 0.723032
#> LaPlata:Bedon.lag(5) -0.030082 -0.1696050 0.725721
#> LaPlata:LaPlata.lag(1) 0.616669 0.2326526 0.461256
#> LaPlata:LaPlata.lag(2) 0.101628 -0.0132510 0.228367
#> LaPlata:LaPlata.lag(3) 0.118773 0.1482564 0.446112
#> LaPlata:LaPlata.lag(4) 0.028702 -0.1512447 0.168490
#> LaPlata:LaPlata.lag(5) 0.185263 -0.0318407 0.194895
#>
#>
#> Scale parameter:
#> Regime 1:lower Regime 1:upper Regime 2:lower Regime 2:upper
#> Bedon.Bedon 0.27354 0.39351 0.8665 1.3069
#> Bedon.LaPlata 0.26386 0.48355 0.9740 1.6845
#> LaPlata.LaPlata 1.82342 2.73758 5.3554 7.7358
#> Regime 3:lower Regime 3:upper
#> Bedon.Bedon 2.2844 3.2401
#> Bedon.LaPlata 5.5933 8.7679
#> LaPlata.LaPlata 33.4590 49.6618
###### Example 3: Temperature, precipitation, and two river flows in Iceland
data(iceland.rf)
fit3 <- mtar(~ Jokulsa + Vatnsdalsa | Temperature | Precipitation,
data=iceland.rf, subset={Date<="1974-11-06"}, row.names=Date,
ars=ars(nregim=2,p=15,q=4,d=2), n.burnin=100, n.sim=200,
n.thin=2, dist="Slash")
coda::HPDinterval(fit3)
#>
#> Probability = 0.95
#>
#> Thresholds:
#> lower upper
#> threshold 0.41803 0.86655
#>
#>
#> Autoregressive coefficients:
#> Regime 1:lower Regime 1:upper Regime 2:lower
#> Jokulsa:(Intercept) 2.6352803 3.66254408 -1.4637157
#> Jokulsa:Jokulsa.lag( 1) 0.8437907 0.92908005 0.9247668
#> Jokulsa:Jokulsa.lag( 2) -0.1171200 -0.01924717 -0.2729527
#> Jokulsa:Jokulsa.lag( 3) -0.0413166 0.03844913 -0.0845591
#> Jokulsa:Jokulsa.lag( 4) -0.0469307 0.06133525 -0.1705010
#> Jokulsa:Jokulsa.lag( 5) -0.0781850 0.04858185 -0.0556182
#> Jokulsa:Jokulsa.lag( 6) -0.0243633 0.08234490 -0.1112915
#> Jokulsa:Jokulsa.lag( 7) -0.0475424 0.06420384 -0.0429613
#> Jokulsa:Jokulsa.lag( 8) -0.0612018 0.03199144 -0.0416531
#> Jokulsa:Jokulsa.lag( 9) -0.0274422 0.05362413 -0.0407820
#> Jokulsa:Jokulsa.lag(10) -0.0116928 0.05011703 -0.0977940
#> Jokulsa:Jokulsa.lag(11) -0.0494385 0.00969262 -0.0803227
#> Jokulsa:Jokulsa.lag(12) -0.0226524 0.03457533 -0.0695737
#> Jokulsa:Jokulsa.lag(13) -0.0482260 0.02412159 -0.0772444
#> Jokulsa:Jokulsa.lag(14) -0.0287629 0.03105070 -0.0850382
#> Jokulsa:Jokulsa.lag(15) -0.0254946 0.03399619 -0.0020238
#> Jokulsa:Vatnsdalsa.lag( 1) 0.1665282 0.39398311 0.5726819
#> Jokulsa:Vatnsdalsa.lag( 2) -0.3908305 -0.11848494 -0.9391427
#> Jokulsa:Vatnsdalsa.lag( 3) -0.0090923 0.16924670 -0.4796786
#> Jokulsa:Vatnsdalsa.lag( 4) -0.1048404 0.05623135 -0.5192297
#> Jokulsa:Vatnsdalsa.lag( 5) -0.1001824 0.02803130 -0.2822171
#> Jokulsa:Vatnsdalsa.lag( 6) -0.0888830 0.09212607 -0.4621238
#> Jokulsa:Vatnsdalsa.lag( 7) -0.0733733 0.08428558 -0.2222564
#> Jokulsa:Vatnsdalsa.lag( 8) -0.0599098 0.06025988 -0.6075366
#> Jokulsa:Vatnsdalsa.lag( 9) -0.0864107 0.03653510 -0.1577563
#> Jokulsa:Vatnsdalsa.lag(10) -0.0105143 0.11175174 -0.4211493
#> Jokulsa:Vatnsdalsa.lag(11) -0.0681296 0.03992450 -0.3725198
#> Jokulsa:Vatnsdalsa.lag(12) -0.0425968 0.05942225 -0.4250372
#> Jokulsa:Vatnsdalsa.lag(13) -0.0784026 0.03363987 -0.1404644
#> Jokulsa:Vatnsdalsa.lag(14) -0.0381498 0.06059892 -0.0822144
#> Jokulsa:Vatnsdalsa.lag(15) -0.0461124 0.02789297 -0.7287150
#> Jokulsa:Precipitation.lag(1) -0.0152452 0.01725471 -0.1658716
#> Jokulsa:Precipitation.lag(2) -0.0082416 0.02147151 -0.1021646
#> Jokulsa:Precipitation.lag(3) -0.0253451 -0.00390403 -0.0302333
#> Jokulsa:Precipitation.lag(4) 0.0089095 0.03699413 -0.0265126
#> Jokulsa:Temperature.lag(1) -0.0046867 0.03373905 0.9100702
#> Jokulsa:Temperature.lag(2) -0.0478685 -0.01039604 -0.6999888
#> Vatnsdalsa:(Intercept) 0.3379556 1.12586285 0.2940713
#> Vatnsdalsa:Jokulsa.lag( 1) -0.0903184 -0.01404886 -0.0122452
#> Vatnsdalsa:Jokulsa.lag( 2) 0.0208662 0.08050007 0.0031973
#> Vatnsdalsa:Jokulsa.lag( 3) -0.0563779 -0.00755996 -0.0280840
#> Vatnsdalsa:Jokulsa.lag( 4) -0.0105903 0.03447163 -0.0047981
#> Vatnsdalsa:Jokulsa.lag( 5) -0.0230110 0.03593609 -0.0131507
#> Vatnsdalsa:Jokulsa.lag( 6) -0.0237673 0.03765377 -0.0038635
#> Vatnsdalsa:Jokulsa.lag( 7) -0.0298951 0.03352870 -0.0154112
#> Vatnsdalsa:Jokulsa.lag( 8) -0.0442377 0.00591719 -0.0049800
#> Vatnsdalsa:Jokulsa.lag( 9) -0.0035092 0.05344896 -0.0121555
#> Vatnsdalsa:Jokulsa.lag(10) -0.0425853 -0.00020858 -0.0062544
#> Vatnsdalsa:Jokulsa.lag(11) -0.0097757 0.02636419 -0.0177264
#> Vatnsdalsa:Jokulsa.lag(12) -0.0310775 0.01196345 0.0017130
#> Vatnsdalsa:Jokulsa.lag(13) -0.0135282 0.03222243 -0.0177952
#> Vatnsdalsa:Jokulsa.lag(14) -0.0256372 0.01167690 -0.0136469
#> Vatnsdalsa:Jokulsa.lag(15) -0.0097672 0.01618842 -0.0033411
#> Vatnsdalsa:Vatnsdalsa.lag( 1) 1.0689326 1.25821080 1.1496467
#> Vatnsdalsa:Vatnsdalsa.lag( 2) -0.4277818 -0.21554767 -0.4633306
#> Vatnsdalsa:Vatnsdalsa.lag( 3) -0.0070751 0.14047505 0.0467195
#> Vatnsdalsa:Vatnsdalsa.lag( 4) -0.0736115 0.04423797 -0.1415051
#> Vatnsdalsa:Vatnsdalsa.lag( 5) -0.0558581 0.04017088 -0.1127569
#> Vatnsdalsa:Vatnsdalsa.lag( 6) -0.0580280 0.04183497 -0.0544863
#> Vatnsdalsa:Vatnsdalsa.lag( 7) -0.0239461 0.05162062 -0.0950839
#> Vatnsdalsa:Vatnsdalsa.lag( 8) -0.0273196 0.03857800 -0.1450165
#> Vatnsdalsa:Vatnsdalsa.lag( 9) -0.0501357 0.02830978 0.0574632
#> Vatnsdalsa:Vatnsdalsa.lag(10) -0.0252365 0.05247966 -0.1257649
#> Vatnsdalsa:Vatnsdalsa.lag(11) -0.0340026 0.03723716 -0.0159824
#> Vatnsdalsa:Vatnsdalsa.lag(12) -0.0423899 0.02643856 -0.1291236
#> Vatnsdalsa:Vatnsdalsa.lag(13) -0.0765034 0.00845364 0.0913001
#> Vatnsdalsa:Vatnsdalsa.lag(14) 0.0016489 0.07722171 -0.0965910
#> Vatnsdalsa:Vatnsdalsa.lag(15) -0.0276669 0.02490403 -0.0850782
#> Vatnsdalsa:Precipitation.lag(1) -0.0067250 0.01585369 -0.0149386
#> Vatnsdalsa:Precipitation.lag(2) -0.0059698 0.01242473 -0.0209657
#> Vatnsdalsa:Precipitation.lag(3) -0.0114683 0.00394847 -0.0057700
#> Vatnsdalsa:Precipitation.lag(4) -0.0018192 0.01752300 -0.0048399
#> Vatnsdalsa:Temperature.lag(1) -0.0147280 0.01293785 0.0113871
#> Vatnsdalsa:Temperature.lag(2) -0.0225938 0.00728257 -0.0737167
#> Regime 2:upper
#> Jokulsa:(Intercept) 1.0598e+00
#> Jokulsa:Jokulsa.lag( 1) 1.0597e+00
#> Jokulsa:Jokulsa.lag( 2) -2.6839e-02
#> Jokulsa:Jokulsa.lag( 3) 1.2141e-01
#> Jokulsa:Jokulsa.lag( 4) -9.9932e-06
#> Jokulsa:Jokulsa.lag( 5) 1.0232e-01
#> Jokulsa:Jokulsa.lag( 6) 1.3155e-02
#> Jokulsa:Jokulsa.lag( 7) 5.5940e-02
#> Jokulsa:Jokulsa.lag( 8) 6.3851e-02
#> Jokulsa:Jokulsa.lag( 9) 9.9867e-02
#> Jokulsa:Jokulsa.lag(10) 6.9948e-02
#> Jokulsa:Jokulsa.lag(11) 7.0507e-02
#> Jokulsa:Jokulsa.lag(12) 7.0307e-02
#> Jokulsa:Jokulsa.lag(13) 8.0591e-02
#> Jokulsa:Jokulsa.lag(14) 7.8418e-02
#> Jokulsa:Jokulsa.lag(15) 9.9372e-02
#> Jokulsa:Vatnsdalsa.lag( 1) 1.3748e+00
#> Jokulsa:Vatnsdalsa.lag( 2) 1.4256e-01
#> Jokulsa:Vatnsdalsa.lag( 3) 6.4760e-01
#> Jokulsa:Vatnsdalsa.lag( 4) 3.1479e-01
#> Jokulsa:Vatnsdalsa.lag( 5) 7.0462e-01
#> Jokulsa:Vatnsdalsa.lag( 6) 2.7482e-01
#> Jokulsa:Vatnsdalsa.lag( 7) 4.6441e-01
#> Jokulsa:Vatnsdalsa.lag( 8) 8.4844e-02
#> Jokulsa:Vatnsdalsa.lag( 9) 6.6999e-01
#> Jokulsa:Vatnsdalsa.lag(10) 2.4466e-01
#> Jokulsa:Vatnsdalsa.lag(11) 5.2024e-01
#> Jokulsa:Vatnsdalsa.lag(12) 3.4087e-01
#> Jokulsa:Vatnsdalsa.lag(13) 7.7751e-01
#> Jokulsa:Vatnsdalsa.lag(14) 6.5356e-01
#> Jokulsa:Vatnsdalsa.lag(15) -1.8925e-01
#> Jokulsa:Precipitation.lag(1) -1.9493e-02
#> Jokulsa:Precipitation.lag(2) 1.1580e-01
#> Jokulsa:Precipitation.lag(3) 9.6531e-02
#> Jokulsa:Precipitation.lag(4) 1.0692e-01
#> Jokulsa:Temperature.lag(1) 1.2490e+00
#> Jokulsa:Temperature.lag(2) -3.6949e-01
#> Vatnsdalsa:(Intercept) 6.7064e-01
#> Vatnsdalsa:Jokulsa.lag( 1) 1.8742e-03
#> Vatnsdalsa:Jokulsa.lag( 2) 2.6314e-02
#> Vatnsdalsa:Jokulsa.lag( 3) -3.1653e-03
#> Vatnsdalsa:Jokulsa.lag( 4) 1.5294e-02
#> Vatnsdalsa:Jokulsa.lag( 5) 5.0599e-03
#> Vatnsdalsa:Jokulsa.lag( 6) 1.1655e-02
#> Vatnsdalsa:Jokulsa.lag( 7) 2.4264e-03
#> Vatnsdalsa:Jokulsa.lag( 8) 1.3611e-02
#> Vatnsdalsa:Jokulsa.lag( 9) 5.0010e-03
#> Vatnsdalsa:Jokulsa.lag(10) 1.3624e-02
#> Vatnsdalsa:Jokulsa.lag(11) 3.3468e-03
#> Vatnsdalsa:Jokulsa.lag(12) 2.0761e-02
#> Vatnsdalsa:Jokulsa.lag(13) 1.7539e-03
#> Vatnsdalsa:Jokulsa.lag(14) 8.1031e-03
#> Vatnsdalsa:Jokulsa.lag(15) 9.3300e-03
#> Vatnsdalsa:Vatnsdalsa.lag( 1) 1.3050e+00
#> Vatnsdalsa:Vatnsdalsa.lag( 2) -2.3812e-01
#> Vatnsdalsa:Vatnsdalsa.lag( 3) 2.4274e-01
#> Vatnsdalsa:Vatnsdalsa.lag( 4) 5.0025e-03
#> Vatnsdalsa:Vatnsdalsa.lag( 5) 8.8094e-02
#> Vatnsdalsa:Vatnsdalsa.lag( 6) 1.2427e-01
#> Vatnsdalsa:Vatnsdalsa.lag( 7) 3.5810e-02
#> Vatnsdalsa:Vatnsdalsa.lag( 8) -2.6445e-02
#> Vatnsdalsa:Vatnsdalsa.lag( 9) 2.0275e-01
#> Vatnsdalsa:Vatnsdalsa.lag(10) -5.1197e-03
#> Vatnsdalsa:Vatnsdalsa.lag(11) 1.1949e-01
#> Vatnsdalsa:Vatnsdalsa.lag(12) 1.3726e-02
#> Vatnsdalsa:Vatnsdalsa.lag(13) 2.1269e-01
#> Vatnsdalsa:Vatnsdalsa.lag(14) 2.5396e-02
#> Vatnsdalsa:Vatnsdalsa.lag(15) 7.3882e-03
#> Vatnsdalsa:Precipitation.lag(1) 8.2376e-03
#> Vatnsdalsa:Precipitation.lag(2) 1.0166e-02
#> Vatnsdalsa:Precipitation.lag(3) 1.5404e-02
#> Vatnsdalsa:Precipitation.lag(4) 1.2294e-02
#> Vatnsdalsa:Temperature.lag(1) 6.5699e-02
#> Vatnsdalsa:Temperature.lag(2) -1.6367e-02
#>
#>
#> Scale parameter:
#> Regime 1:lower Regime 1:upper Regime 2:lower
#> Jokulsa.Jokulsa 0.0441134 0.080208 0.856745
#> Jokulsa.Vatnsdalsa 0.0041052 0.014284 0.018497
#> Vatnsdalsa.Vatnsdalsa 0.0190521 0.033208 0.016256
#> Regime 2:upper
#> Jokulsa.Jokulsa 1.845408
#> Jokulsa.Vatnsdalsa 0.077260
#> Vatnsdalsa.Vatnsdalsa 0.042387
#>
#>
#> Extra parameter:
#> lower upper
#> nu 0.74422 0.91488
###### Example 4: U.S. stock returns
data(US.returns)
fit4 <- mtar(~ CCR | dVIX, data=US.returns, subset={Date<="2025-11-28"},
row.names=Date, ars=ars(nregim=2,p=3,d=3), n.burnin=100,
n.sim=200, n.thin=2, dist="Student-t")
coda::HPDinterval(fit4)
#>
#> Probability = 0.95
#>
#> Thresholds:
#> lower upper
#> threshold 1.8713 2.1709
#>
#>
#> Autoregressive coefficients:
#> Regime 1:lower Regime 1:upper Regime 2:lower Regime 2:upper
#> CCR:(Intercept) 0.0668979 0.1127371 -0.4113077 0.157977
#> CCR:CCR.lag(1) -0.0743691 -0.0276331 -0.2999127 -0.028327
#> CCR:CCR.lag(2) -0.0726077 -0.0023142 -0.2478509 0.173860
#> CCR:CCR.lag(3) -0.0705618 0.0075159 -0.0316060 0.370194
#> CCR:dVIX.lag(1) -0.0549186 -0.0043995 -0.1778912 0.104887
#> CCR:dVIX.lag(2) -0.0520714 -0.0034718 -0.0321339 0.173310
#> CCR:dVIX.lag(3) -0.0025748 0.0277559 -0.0022731 0.137239
#>
#>
#> Scale parameter:
#> Regime 1:lower Regime 1:upper Regime 2:lower Regime 2:upper
#> CCR.CCR 0.3385 0.39313 0.8436 1.3108
#>
#>
#> Extra parameter:
#> lower upper
#> nu 2.2695 2.6713
# }