Generate Random Drift Matrices and Process Noise Covariance Matrices Using the Monte Carlo Method
Source:R/cTMed-mc-phi-sigma.R
MCPhiSigma.RdThis function generates random drift matrices \(\boldsymbol{\Phi}\) and process noise covariabces matrices \(\boldsymbol{\Sigma}\) using the Monte Carlo method.
Arguments
- phi
Numeric matrix. The drift matrix (\(\boldsymbol{\Phi}\)).
phishould have row and column names pertaining to the variables in the system.- sigma
Numeric matrix. The process noise covariance matrix (\(\boldsymbol{\Sigma}\)).
- vcov_theta
Numeric matrix. The sampling variance-covariance matrix of \(\mathrm{vec} \left( \boldsymbol{\Phi} \right)\) and \(\mathrm{vech} \left( \boldsymbol{\Sigma} \right)\)
- R
Positive integer. Number of replications.
- test_phi
Logical. If
test_phi = TRUE, the function tests the stability of the generated drift matrix \(\boldsymbol{\Phi}\). If the test returnsFALSE, the function generates a new drift matrix \(\boldsymbol{\Phi}\) and runs the test recursively until the test returnsTRUE.- ncores
Positive integer. Number of cores to use. If
ncores = NULL, use a single core. Consider using multiple cores when number of replicationsRis a large value.- seed
Random seed.
Value
Returns an object
of class ctmedmc which is a list with the following elements:
- call
Function call.
- args
Function arguments.
- fun
Function used ("MCPhiSigma").
- output
A list simulated drift matrices.
Details
Monte Carlo Method
Let \(\boldsymbol{\theta}\) be a vector that combines \(\mathrm{vec} \left( \boldsymbol{\Phi} \right)\), that is, the elements of the \(\boldsymbol{\Phi}\) matrix in vector form sorted column-wise and \(\mathrm{vech} \left( \boldsymbol{\Sigma} \right)\), that is, the unique elements of the \(\boldsymbol{\Sigma}\) matrix in vector form sorted column-wise. Let \(\hat{\boldsymbol{\theta}}\) be a vector that combines \(\mathrm{vec} \left( \hat{\boldsymbol{\Phi}} \right)\) and \(\mathrm{vech} \left( \hat{\boldsymbol{\Sigma}} \right)\). Based on the asymptotic properties of maximum likelihood estimators, we can assume that estimators are normally distributed around the population parameters. $$ \hat{\boldsymbol{\theta}} \sim \mathcal{N} \left( \boldsymbol{\theta}, \mathbb{V} \left( \hat{\boldsymbol{\theta}} \right) \right) $$ Using this distributional assumption, a sampling distribution of \(\hat{\boldsymbol{\theta}}\) which we refer to as \(\hat{\boldsymbol{\theta}}^{\ast}\) can be generated by replacing the population parameters with sample estimates, that is, $$ \hat{\boldsymbol{\theta}}^{\ast} \sim \mathcal{N} \left( \hat{\boldsymbol{\theta}}, \hat{\mathbb{V}} \left( \hat{\boldsymbol{\theta}} \right) \right) . $$
See also
Other Continuous Time Mediation Functions:
BootBeta(),
BootBetaStd(),
BootIndirectCentral(),
BootMed(),
BootMedStd(),
BootTotalCentral(),
DeltaBeta(),
DeltaBetaStd(),
DeltaIndirectCentral(),
DeltaMed(),
DeltaMedStd(),
DeltaTotalCentral(),
Direct(),
DirectStd(),
ExpCov(),
ExpMean(),
Indirect(),
IndirectCentral(),
IndirectStd(),
MCBeta(),
MCBetaStd(),
MCIndirectCentral(),
MCMed(),
MCMedStd(),
MCPhi(),
MCTotalCentral(),
Med(),
MedStd(),
PosteriorBeta(),
PosteriorIndirectCentral(),
PosteriorMed(),
PosteriorTotalCentral(),
Total(),
TotalCentral(),
TotalStd(),
Trajectory()
Examples
set.seed(42)
phi <- matrix(
data = c(
-0.357, 0.771, -0.450,
0.0, -0.511, 0.729,
0, 0, -0.693
),
nrow = 3
)
colnames(phi) <- rownames(phi) <- c("x", "m", "y")
sigma <- matrix(
data = c(
0.24455556, 0.02201587, -0.05004762,
0.02201587, 0.07067800, 0.01539456,
-0.05004762, 0.01539456, 0.07553061
),
nrow = 3
)
MCPhiSigma(
phi = phi,
sigma = sigma,
vcov_theta = 0.1 * diag(15),
R = 100L # use a large value for R in actual research
)
#> [[1]]
#> [[1]][[1]]
#> x m y
#> x -0.0957 0.0263 -0.1507
#> m 0.8653 -0.9254 0.4226
#> y -0.3456 0.3478 -0.5309
#>
#> [[1]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2084 -0.3647 -0.0479
#> [2,] -0.3647 0.6456 0.1214
#> [3,] -0.0479 0.1214 0.2013
#>
#>
#> [[2]]
#> [[2]][[1]]
#> x m y
#> x -0.5278 -0.3347 -0.2763
#> m 1.0161 -0.9849 0.2003
#> y -0.2007 0.6946 -0.6920
#>
#> [[2]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2782 -0.0617 -0.3256
#> [2,] -0.0617 0.0901 0.2183
#> [3,] -0.3256 0.2183 0.6601
#>
#>
#> [[3]]
#> [[3]][[1]]
#> x m y
#> x -0.4018 -0.1907 -0.0677
#> m 0.7344 -1.3231 -0.3393
#> y 0.0472 0.5430 -0.3117
#>
#> [[3]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4038 0.1140 0.0883
#> [2,] 0.1140 0.1321 -0.1766
#> [3,] 0.0883 -0.1766 0.4256
#>
#>
#> [[4]]
#> [[4]][[1]]
#> x m y
#> x -0.5798 0.1835 0.2893
#> m 0.6420 -0.4850 0.2752
#> y -0.6472 0.4132 -0.3708
#>
#> [[4]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3617 0.1826 -0.1071
#> [2,] 0.1826 0.0922 -0.0521
#> [3,] -0.1071 -0.0521 0.2382
#>
#>
#> [[5]]
#> [[5]][[1]]
#> x m y
#> x -0.5308 -0.2971 0.4638
#> m 1.0700 -0.6486 -0.6680
#> y -0.6323 0.4139 -0.9234
#>
#> [[5]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6437 0.5209 -0.2458
#> [2,] 0.5209 0.4242 -0.1904
#> [3,] -0.2458 -0.1904 0.1198
#>
#>
#> [[6]]
#> [[6]][[1]]
#> x m y
#> x -0.5323 0.0733 0.3680
#> m 0.4414 -0.8219 0.6145
#> y -0.9988 0.7608 -0.5748
#>
#> [[6]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0384 -0.0341 0.0446
#> [2,] -0.0341 0.1952 -0.2344
#> [3,] 0.0446 -0.2344 0.2820
#>
#>
#> [[7]]
#> [[7]][[1]]
#> x m y
#> x -0.4964 -0.3485 -0.5275
#> m 0.8803 -0.2652 -0.2808
#> y -0.4947 0.6248 -0.8066
#>
#> [[7]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0219 0.0470 -0.0699
#> [2,] 0.0470 0.1010 -0.1503
#> [3,] -0.0699 -0.1503 0.2237
#>
#>
#> [[8]]
#> [[8]][[1]]
#> x m y
#> x -0.3729 0.1268 -0.0831
#> m 0.7244 -1.0035 -0.2035
#> y -0.2491 0.4263 -0.2417
#>
#> [[8]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.7350 -0.1220 -0.5629
#> [2,] -0.1220 0.0203 0.0935
#> [3,] -0.5629 0.0935 0.4311
#>
#>
#> [[9]]
#> [[9]][[1]]
#> x m y
#> x -0.7018 -0.287 -0.4060
#> m 0.4014 -0.926 -0.6191
#> y -0.4522 1.042 -0.9174
#>
#> [[9]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1100 0.0805 0.1586
#> [2,] 0.0805 0.1239 0.2240
#> [3,] 0.1586 0.2240 0.4082
#>
#>
#> [[10]]
#> [[10]][[1]]
#> x m y
#> x -0.7130 -0.0718 0.2803
#> m 0.6654 -0.3968 -0.1850
#> y 0.1915 0.1108 -0.7506
#>
#> [[10]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2025 0.2538 -0.0539
#> [2,] 0.2538 0.3182 -0.0676
#> [3,] -0.0539 -0.0676 0.0143
#>
#>
#> [[11]]
#> [[11]][[1]]
#> x m y
#> x -0.3922 -0.0144 -0.1370
#> m 0.5602 -0.4864 -0.6544
#> y -0.7721 0.4842 -0.0734
#>
#> [[11]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6277 0.1112 0.4736
#> [2,] 0.1112 0.1715 0.0026
#> [3,] 0.4736 0.0026 0.4009
#>
#>
#> [[12]]
#> [[12]][[1]]
#> x m y
#> x -0.6543 0.1989 -0.5933
#> m 0.7583 -0.6301 -0.1023
#> y -0.3791 1.0368 -0.8090
#>
#> [[12]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3449 0.0936 -0.1936
#> [2,] 0.0936 0.1728 -0.3292
#> [3,] -0.1936 -0.3292 0.6279
#>
#>
#> [[13]]
#> [[13]][[1]]
#> x m y
#> x -0.6089 0.2607 -0.2650
#> m 0.2459 -0.5695 0.0963
#> y -0.8200 0.4991 -0.8746
#>
#> [[13]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0530 -0.1447 0.1748
#> [2,] -0.1447 0.3952 -0.4775
#> [3,] 0.1748 -0.4775 0.5768
#>
#>
#> [[14]]
#> [[14]][[1]]
#> x m y
#> x -0.9407 0.4237 0.1673
#> m 1.0778 -0.5615 -0.1271
#> y -0.1173 0.1810 -0.3245
#>
#> [[14]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4544 -0.0291 -0.2844
#> [2,] -0.0291 0.0261 0.0182
#> [3,] -0.2844 0.0182 0.1780
#>
#>
#> [[15]]
#> [[15]][[1]]
#> x m y
#> x -0.7717 -0.2800 0.1728
#> m 0.4799 -0.4767 -0.3760
#> y -0.1823 1.2392 -1.0738
#>
#> [[15]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5964 0.4158 0.3092
#> [2,] 0.4158 0.3037 0.1452
#> [3,] 0.3092 0.1452 0.5176
#>
#>
#> [[16]]
#> [[16]][[1]]
#> x m y
#> x -0.6313 0.1458 0.5649
#> m 1.0035 -1.0179 -0.0652
#> y -0.7079 0.5710 -0.9275
#>
#> [[16]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0950 -0.2015 -0.1425
#> [2,] -0.2015 0.4275 0.3022
#> [3,] -0.1425 0.3022 0.2137
#>
#>
#> [[17]]
#> [[17]][[1]]
#> x m y
#> x -0.6305 0.0519 -0.3075
#> m 0.2891 -0.8919 -0.1079
#> y -0.5822 0.8868 -0.8725
#>
#> [[17]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6199 -0.4343 -0.4270
#> [2,] -0.4343 0.3042 0.2992
#> [3,] -0.4270 0.2992 0.2942
#>
#>
#> [[18]]
#> [[18]][[1]]
#> x m y
#> x -0.4866 -0.1255 0.3668
#> m 0.3933 -0.4558 0.3564
#> y -0.6396 0.3644 -0.4484
#>
#> [[18]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4905 -0.4313 0.2472
#> [2,] -0.4313 0.3793 -0.2173
#> [3,] 0.2472 -0.2173 0.1246
#>
#>
#> [[19]]
#> [[19]][[1]]
#> x m y
#> x -0.2808 0.0457 0.0345
#> m 0.6865 -0.4855 -0.4860
#> y -0.8859 0.3376 -1.2683
#>
#> [[19]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4990 0.0736 0.3997
#> [2,] 0.0736 0.5316 0.1545
#> [3,] 0.3997 0.1545 0.3377
#>
#>
#> [[20]]
#> [[20]][[1]]
#> x m y
#> x -0.7559 -0.1536 0.4511
#> m 0.9942 -0.9598 0.5648
#> y -0.4914 0.5642 -1.0631
#>
#> [[20]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5334 0.1472 0.1451
#> [2,] 0.1472 0.0407 0.0434
#> [3,] 0.1451 0.0434 0.1142
#>
#>
#> [[21]]
#> [[21]][[1]]
#> x m y
#> x -0.7730 -0.1430 -0.5482
#> m 0.4954 -0.4709 -0.1641
#> y -0.3138 1.2306 -0.6674
#>
#> [[21]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1942 0.0945 0.1136
#> [2,] 0.0945 0.1199 0.0997
#> [3,] 0.1136 0.0997 0.0931
#>
#>
#> [[22]]
#> [[22]][[1]]
#> x m y
#> x -0.4945 -0.6671 -0.3027
#> m 1.0400 -0.4402 0.5274
#> y -0.5167 0.8127 -1.0204
#>
#> [[22]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2571 0.2225 0.0012
#> [2,] 0.2225 0.2074 0.0620
#> [3,] 0.0012 0.0620 0.2486
#>
#>
#> [[23]]
#> [[23]][[1]]
#> x m y
#> x -0.2055 -0.1266 -0.0666
#> m 0.9118 -0.0650 0.2347
#> y -0.9983 0.2717 -0.7472
#>
#> [[23]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2463 0.2005 0.1557
#> [2,] 0.2005 0.1994 0.0751
#> [3,] 0.1557 0.0751 0.1725
#>
#>
#> [[24]]
#> [[24]][[1]]
#> x m y
#> x -0.5935 -0.3221 0.2496
#> m 0.3853 -0.8539 0.2454
#> y -0.4149 0.2561 -0.7975
#>
#> [[24]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2061 0.0352 0.0933
#> [2,] 0.0352 0.0060 0.0159
#> [3,] 0.0933 0.0159 0.0422
#>
#>
#> [[25]]
#> [[25]][[1]]
#> x m y
#> x -0.3634 -0.0708 -0.3003
#> m 0.9753 -0.7200 1.1534
#> y -0.4025 0.9655 -0.8761
#>
#> [[25]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3494 0.3209 -0.1330
#> [2,] 0.3209 0.2948 -0.1221
#> [3,] -0.1330 -0.1221 0.0506
#>
#>
#> [[26]]
#> [[26]][[1]]
#> x m y
#> x -0.8219 -0.2116 -0.0700
#> m 0.4884 -0.5324 0.4498
#> y -0.3297 0.5871 -0.7476
#>
#> [[26]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0223 -0.0503 0.0619
#> [2,] -0.0503 0.1531 -0.1182
#> [3,] 0.0619 -0.1182 0.1828
#>
#>
#> [[27]]
#> [[27]][[1]]
#> x m y
#> x -0.3332 -0.0772 -0.0003
#> m 0.5535 -0.0950 -0.1349
#> y -0.4507 0.7802 -0.5585
#>
#> [[27]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.8069 -0.0618 0.1021
#> [2,] -0.0618 0.0854 0.1171
#> [3,] 0.1021 0.1171 0.2064
#>
#>
#> [[28]]
#> [[28]][[1]]
#> x m y
#> x -0.4629 -0.1020 -0.3401
#> m 0.8775 -0.2102 -0.4043
#> y -0.6210 0.5264 -0.9892
#>
#> [[28]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1603 -0.0459 -0.2213
#> [2,] -0.0459 0.0131 0.0633
#> [3,] -0.2213 0.0633 0.3055
#>
#>
#> [[29]]
#> [[29]][[1]]
#> x m y
#> x -0.3671 -0.0507 0.2011
#> m 0.4971 -0.9741 -0.2671
#> y -0.3027 1.1691 -0.6000
#>
#> [[29]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6322 0.1248 -0.1469
#> [2,] 0.1248 0.0247 -0.0290
#> [3,] -0.1469 -0.0290 0.0342
#>
#>
#> [[30]]
#> [[30]][[1]]
#> x m y
#> x -0.2002 0.1459 -0.2178
#> m 0.1059 -0.4572 -0.0207
#> y -0.2826 1.2068 -0.9261
#>
#> [[30]][[2]]
#> [,1] [,2] [,3]
#> [1,] 1.0116 -0.0162 -0.1021
#> [2,] -0.0162 0.0003 0.0016
#> [3,] -0.1021 0.0016 0.0103
#>
#>
#> [[31]]
#> [[31]][[1]]
#> x m y
#> x -0.5716 -0.2904 -0.9815
#> m 0.6002 -0.5104 0.3351
#> y -0.5145 0.9666 -0.5926
#>
#> [[31]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5471 0.1585 -0.4529
#> [2,] 0.1585 0.0459 -0.1312
#> [3,] -0.4529 -0.1312 0.3749
#>
#>
#> [[32]]
#> [[32]][[1]]
#> x m y
#> x -0.7341 -0.0446 -0.5146
#> m 1.0279 -0.0788 -0.2571
#> y -0.6199 0.7966 -0.7640
#>
#> [[32]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4086 0.2762 -0.4548
#> [2,] 0.2762 0.1867 -0.3074
#> [3,] -0.4548 -0.3074 0.5061
#>
#>
#> [[33]]
#> [[33]][[1]]
#> x m y
#> x -0.0936 -0.1392 0.3097
#> m 1.0521 -0.4798 -0.4324
#> y -0.5027 0.6471 -0.7498
#>
#> [[33]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5477 0.2456 0.1058
#> [2,] 0.2456 0.3927 -0.0594
#> [3,] 0.1058 -0.0594 0.0609
#>
#>
#> [[34]]
#> [[34]][[1]]
#> x m y
#> x -0.0528 -0.0732 -0.4617
#> m 0.8469 -0.8229 -0.0929
#> y -0.2442 1.0004 -0.3120
#>
#> [[34]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5940 -0.1519 0.1558
#> [2,] -0.1519 0.0918 -0.1974
#> [3,] 0.1558 -0.1974 0.5098
#>
#>
#> [[35]]
#> [[35]][[1]]
#> x m y
#> x -0.6377 0.0118 -0.2127
#> m 0.4611 -0.0850 0.0130
#> y -0.4858 0.9554 -0.8258
#>
#> [[35]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1715 0.1234 -0.1656
#> [2,] 0.1234 0.4647 -0.5007
#> [3,] -0.1656 -0.5007 0.5472
#>
#>
#> [[36]]
#> [[36]][[1]]
#> x m y
#> x -0.3556 -0.0205 -0.0255
#> m 1.1865 -0.1943 -0.0506
#> y -0.7327 0.6756 -1.0600
#>
#> [[36]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.7062 -0.3264 -0.0720
#> [2,] -0.3264 0.3677 -0.2076
#> [3,] -0.0720 -0.2076 0.2748
#>
#>
#> [[37]]
#> [[37]][[1]]
#> x m y
#> x -0.4298 -0.0444 -0.4327
#> m 0.8583 -0.2174 0.1232
#> y -0.5062 0.4359 -0.9625
#>
#> [[37]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2513 -0.0211 0.1160
#> [2,] -0.0211 0.0018 -0.0098
#> [3,] 0.1160 -0.0098 0.0536
#>
#>
#> [[38]]
#> [[38]][[1]]
#> x m y
#> x -0.7014 0.3487 -0.0053
#> m 0.7319 -1.2244 0.1098
#> y -0.5596 0.4242 -0.8731
#>
#> [[38]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0633 0.0811 0.0452
#> [2,] 0.0811 0.1040 0.0579
#> [3,] 0.0452 0.0579 0.0323
#>
#>
#> [[39]]
#> [[39]][[1]]
#> x m y
#> x -0.5995 -0.4198 -0.5094
#> m 0.6576 -0.2874 0.3968
#> y -0.2405 0.7774 -0.6126
#>
#> [[39]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5414 0.1288 0.2492
#> [2,] 0.1288 0.3167 0.0554
#> [3,] 0.2492 0.0554 0.5313
#>
#>
#> [[40]]
#> [[40]][[1]]
#> x m y
#> x -0.8816 -0.1537 0.1903
#> m 0.6856 -0.5012 0.0072
#> y -0.1474 1.2228 -1.0138
#>
#> [[40]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2999 -0.0386 -0.0075
#> [2,] -0.0386 0.3005 -0.0819
#> [3,] -0.0075 -0.0819 0.0234
#>
#>
#> [[41]]
#> [[41]][[1]]
#> x m y
#> x -0.3246 -0.2059 -0.0913
#> m 0.9513 -0.5399 -0.5873
#> y 0.0404 1.3811 -0.5884
#>
#> [[41]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.7772 0.2049 0.1479
#> [2,] 0.2049 0.0884 0.0603
#> [3,] 0.1479 0.0603 0.0414
#>
#>
#> [[42]]
#> [[42]][[1]]
#> x m y
#> x -0.4740 0.4396 -0.0832
#> m 0.6544 -0.7612 0.3754
#> y -0.2096 0.5643 -0.9836
#>
#> [[42]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4298 0.2421 0.1416
#> [2,] 0.2421 0.1725 0.2533
#> [3,] 0.1416 0.2533 0.8802
#>
#>
#> [[43]]
#> [[43]][[1]]
#> x m y
#> x -0.1173 -0.0902 0.1875
#> m 1.1948 -1.0243 -0.2334
#> y -0.7911 1.4457 -0.8459
#>
#> [[43]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4451 0.3015 -0.2017
#> [2,] 0.3015 0.2045 -0.1427
#> [3,] -0.2017 -0.1427 0.2367
#>
#>
#> [[44]]
#> [[44]][[1]]
#> x m y
#> x -0.4710 -0.3980 0.3124
#> m 0.4508 -0.4456 -0.1643
#> y -0.3165 0.3697 -0.7265
#>
#> [[44]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4850 0.4859 -0.0714
#> [2,] 0.4859 0.4867 -0.0716
#> [3,] -0.0714 -0.0716 0.0105
#>
#>
#> [[45]]
#> [[45]][[1]]
#> x m y
#> x -0.4309 -0.1042 -0.0629
#> m 0.7116 -0.6306 0.1055
#> y -0.4704 0.3523 -0.9833
#>
#> [[45]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3105 0.0843 -0.3497
#> [2,] 0.0843 0.1367 -0.0448
#> [3,] -0.3497 -0.0448 0.4159
#>
#>
#> [[46]]
#> [[46]][[1]]
#> x m y
#> x -0.0051 -0.2148 -0.0709
#> m 1.0329 -0.1408 0.0182
#> y -0.4525 0.5266 -0.7625
#>
#> [[46]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2581 0.1793 -0.3177
#> [2,] 0.1793 0.1246 -0.2207
#> [3,] -0.3177 -0.2207 0.3910
#>
#>
#> [[47]]
#> [[47]][[1]]
#> x m y
#> x -0.4616 -0.0725 0.0428
#> m 0.6098 -0.6282 0.5300
#> y -0.7799 0.4186 -0.9579
#>
#> [[47]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1560 -0.0425 0.0423
#> [2,] -0.0425 0.3610 -0.2309
#> [3,] 0.0423 -0.2309 0.6432
#>
#>
#> [[48]]
#> [[48]][[1]]
#> x m y
#> x -0.1502 -0.0957 -0.0033
#> m 0.3819 -0.4073 -0.2677
#> y 0.3205 1.1344 -0.9660
#>
#> [[48]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.9879 -0.1351 0.1604
#> [2,] -0.1351 0.1350 -0.0800
#> [3,] 0.1604 -0.0800 0.0550
#>
#>
#> [[49]]
#> [[49]][[1]]
#> x m y
#> x -0.3805 0.0326 0.2706
#> m 0.6879 -0.8394 -0.3294
#> y -0.3198 0.7781 -0.3086
#>
#> [[49]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1539 0.2687 -0.1492
#> [2,] 0.2687 0.6435 -0.4119
#> [3,] -0.1492 -0.4119 0.2760
#>
#>
#> [[50]]
#> [[50]][[1]]
#> x m y
#> x -0.2143 0.0397 -0.3903
#> m 0.4640 -0.6397 0.1573
#> y -0.3312 0.7080 -0.4495
#>
#> [[50]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3515 -0.2139 -0.1041
#> [2,] -0.2139 0.3212 -0.1573
#> [3,] -0.1041 -0.1573 0.2857
#>
#>
#> [[51]]
#> [[51]][[1]]
#> x m y
#> x -0.2475 -0.4155 0.3497
#> m 0.6953 -0.4973 0.1498
#> y -0.3532 0.7291 -0.4281
#>
#> [[51]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4008 0.1479 -0.1788
#> [2,] 0.1479 0.0546 -0.0660
#> [3,] -0.1788 -0.0660 0.0797
#>
#>
#> [[52]]
#> [[52]][[1]]
#> x m y
#> x -0.1458 0.1409 -0.0531
#> m 0.9106 -0.7036 -0.0348
#> y -0.2370 0.8806 -0.7353
#>
#> [[52]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3600 0.0878 -0.0557
#> [2,] 0.0878 0.1881 0.2124
#> [3,] -0.0557 0.2124 0.3151
#>
#>
#> [[53]]
#> [[53]][[1]]
#> x m y
#> x -0.2222 -0.1310 0.2233
#> m 1.0857 -0.6299 0.5893
#> y -0.7770 0.5307 -1.0305
#>
#> [[53]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6087 -0.4546 0.1737
#> [2,] -0.4546 0.3573 -0.2092
#> [3,] 0.1737 -0.2092 0.4051
#>
#>
#> [[54]]
#> [[54]][[1]]
#> x m y
#> x -0.8887 0.2168 -0.1064
#> m 0.5653 -0.6396 -0.0758
#> y -0.3042 0.6632 -0.6685
#>
#> [[54]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1005 -0.1568 -0.1958
#> [2,] -0.1568 0.2448 0.3056
#> [3,] -0.1958 0.3056 0.3816
#>
#>
#> [[55]]
#> [[55]][[1]]
#> x m y
#> x -0.9374 0.4206 0.3723
#> m 0.5856 -0.6921 0.2199
#> y -0.1164 0.9093 -0.9678
#>
#> [[55]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4113 -0.2727 0.0610
#> [2,] -0.2727 0.2883 -0.2670
#> [3,] 0.0610 -0.2670 0.4866
#>
#>
#> [[56]]
#> [[56]][[1]]
#> x m y
#> x -0.2503 -0.5146 -0.1520
#> m 1.1227 -0.6609 0.5791
#> y -0.3941 0.9865 -0.4976
#>
#> [[56]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.7958 -0.5671 -0.3135
#> [2,] -0.5671 0.4042 0.2234
#> [3,] -0.3135 0.2234 0.1235
#>
#>
#> [[57]]
#> [[57]][[1]]
#> x m y
#> x -0.6878 -0.0961 -0.3349
#> m 0.9391 -0.0706 -0.5326
#> y -0.6234 0.9463 -0.9343
#>
#> [[57]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4845 -0.1940 -0.2539
#> [2,] -0.1940 0.7550 0.0008
#> [3,] -0.2539 0.0008 0.6943
#>
#>
#> [[58]]
#> [[58]][[1]]
#> x m y
#> x -0.3363 -0.3818 -0.1050
#> m 1.0383 -0.5745 -0.3098
#> y -0.7873 0.7268 -0.6687
#>
#> [[58]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6970 0.0902 0.1216
#> [2,] 0.0902 0.0818 -0.1256
#> [3,] 0.1216 -0.1256 0.3059
#>
#>
#> [[59]]
#> [[59]][[1]]
#> x m y
#> x -0.6026 -0.4554 0.3668
#> m 0.9719 -0.9901 -0.1138
#> y -0.3521 1.1071 -0.6564
#>
#> [[59]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6601 -0.1795 0.2528
#> [2,] -0.1795 0.0515 -0.0812
#> [3,] 0.2528 -0.0812 0.1553
#>
#>
#> [[60]]
#> [[60]][[1]]
#> x m y
#> x -0.3440 0.1419 -0.0562
#> m 1.0771 -0.7116 -0.0177
#> y -0.4075 0.2834 -1.0193
#>
#> [[60]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2470 -0.2132 -0.1865
#> [2,] -0.2132 0.5927 -0.0580
#> [3,] -0.1865 -0.0580 0.2582
#>
#>
#> [[61]]
#> [[61]][[1]]
#> x m y
#> x -0.3492 0.5789 0.0045
#> m 0.3345 -0.5409 -0.1746
#> y -0.2112 0.8523 -0.5644
#>
#> [[61]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6503 0.1099 -0.3057
#> [2,] 0.1099 0.0724 0.0418
#> [3,] -0.3057 0.0418 0.3061
#>
#>
#> [[62]]
#> [[62]][[1]]
#> x m y
#> x -0.1217 -0.1273 -0.2099
#> m 1.0016 -0.3975 0.1838
#> y -0.0019 1.1542 -0.9609
#>
#> [[62]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3483 0.1607 0.1890
#> [2,] 0.1607 0.2717 0.1950
#> [3,] 0.1890 0.1950 0.1614
#>
#>
#> [[63]]
#> [[63]][[1]]
#> x m y
#> x -0.6779 0.1738 -0.0312
#> m 0.8548 -0.4255 -0.4178
#> y -0.2483 0.4674 -0.7161
#>
#> [[63]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3584 0.1173 -0.0433
#> [2,] 0.1173 0.1364 0.2003
#> [3,] -0.0433 0.2003 0.7328
#>
#>
#> [[64]]
#> [[64]][[1]]
#> x m y
#> x -0.3198 -0.3037 0.3106
#> m 0.8710 -0.7809 -0.0708
#> y -0.0486 0.2357 -1.0363
#>
#> [[64]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6845 -0.2377 -0.5361
#> [2,] -0.2377 0.2679 0.0118
#> [3,] -0.5361 0.0118 0.5839
#>
#>
#> [[65]]
#> [[65]][[1]]
#> x m y
#> x -0.2864 0.3173 -0.1932
#> m 0.3938 -0.3615 -0.0835
#> y -0.6604 0.9228 -0.6961
#>
#> [[65]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1552 -0.1702 0.1947
#> [2,] -0.1702 0.1876 -0.2055
#> [3,] 0.1947 -0.2055 0.3110
#>
#>
#> [[66]]
#> [[66]][[1]]
#> x m y
#> x -0.5653 0.5082 0.1769
#> m 0.2996 -1.0707 0.0119
#> y -0.4249 0.4022 -1.1536
#>
#> [[66]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6602 0.0318 0.2916
#> [2,] 0.0318 0.3417 -0.0354
#> [3,] 0.2916 -0.0354 0.1360
#>
#>
#> [[67]]
#> [[67]][[1]]
#> x m y
#> x -0.8375 -0.3296 0.2027
#> m 1.2818 -0.8500 0.0494
#> y -0.2475 0.4389 -1.2989
#>
#> [[67]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4990 -0.1841 -0.1650
#> [2,] -0.1841 0.0816 0.0937
#> [3,] -0.1650 0.0937 0.1334
#>
#>
#> [[68]]
#> [[68]][[1]]
#> x m y
#> x -0.3728 -0.3627 -0.0973
#> m 0.8306 -0.7333 -0.1693
#> y -0.3713 1.4143 -0.4007
#>
#> [[68]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.8069 0.0429 -0.5716
#> [2,] 0.0429 0.3306 0.0608
#> [3,] -0.5716 0.0608 0.7985
#>
#>
#> [[69]]
#> [[69]][[1]]
#> x m y
#> x -0.1259 -0.6083 0.3736
#> m 0.9839 -0.9559 0.4978
#> y -0.3993 0.6415 -0.4283
#>
#> [[69]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.7396 -0.2474 -0.0459
#> [2,] -0.2474 0.3590 -0.2160
#> [3,] -0.0459 -0.2160 0.1966
#>
#>
#> [[70]]
#> [[70]][[1]]
#> x m y
#> x -0.3332 0.1637 0.3328
#> m 0.6083 -0.6661 -0.0817
#> y -0.3382 0.6261 -0.3247
#>
#> [[70]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0999 -0.1531 0.1656
#> [2,] -0.1531 0.2345 -0.2537
#> [3,] 0.1656 -0.2537 0.2745
#>
#>
#> [[71]]
#> [[71]][[1]]
#> x m y
#> x -0.3295 -0.0327 0.3620
#> m 0.4292 -0.2922 -0.1802
#> y -0.3511 0.5100 -0.7638
#>
#> [[71]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4526 0.0713 -0.3305
#> [2,] 0.0713 0.0325 -0.0575
#> [3,] -0.3305 -0.0575 0.2428
#>
#>
#> [[72]]
#> [[72]][[1]]
#> x m y
#> x -0.7649 0.0023 -0.0388
#> m 0.2166 -0.3383 -0.1438
#> y -0.2593 0.9316 -0.7254
#>
#> [[72]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0 0 0
#> [2,] 0 0 0
#> [3,] 0 0 0
#>
#>
#> [[73]]
#> [[73]][[1]]
#> x m y
#> x -0.3282 -0.1264 -0.1184
#> m 0.7138 -0.9852 -0.2561
#> y -0.8044 0.5748 -1.2341
#>
#> [[73]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.6982 0.4062 0.0483
#> [2,] 0.4062 0.2404 0.0496
#> [3,] 0.0483 0.0496 0.1159
#>
#>
#> [[74]]
#> [[74]][[1]]
#> x m y
#> x -0.0355 -0.1531 -0.0393
#> m 1.0087 -0.5874 -0.0048
#> y -0.5520 0.5136 -0.3720
#>
#> [[74]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1988 -0.2241 0.3197
#> [2,] -0.2241 0.2527 -0.3605
#> [3,] 0.3197 -0.3605 0.5142
#>
#>
#> [[75]]
#> [[75]][[1]]
#> x m y
#> x -0.4091 0.2248 -0.1308
#> m 1.1192 -0.2920 -0.0253
#> y -0.5631 1.3991 -0.6319
#>
#> [[75]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3777 0.0686 0.4435
#> [2,] 0.0686 0.0125 0.0806
#> [3,] 0.4435 0.0806 0.5207
#>
#>
#> [[76]]
#> [[76]][[1]]
#> x m y
#> x -0.4452 0.1454 -0.2587
#> m 0.3094 -0.7091 -0.1579
#> y -0.2925 0.9600 -1.1439
#>
#> [[76]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4494 -0.2002 0.0348
#> [2,] -0.2002 0.0929 0.0395
#> [3,] 0.0348 0.0395 0.8192
#>
#>
#> [[77]]
#> [[77]][[1]]
#> x m y
#> x -0.4079 0.2799 0.1064
#> m 0.4409 -0.5127 -0.2555
#> y -0.1341 0.1615 -1.1697
#>
#> [[77]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.566 -0.3470 -0.0920
#> [2,] -0.347 0.4580 -0.1594
#> [3,] -0.092 -0.1594 0.2049
#>
#>
#> [[78]]
#> [[78]][[1]]
#> x m y
#> x -0.4250 0.1499 -0.1253
#> m 0.7440 -0.5436 -0.2915
#> y -0.3072 0.2398 -0.7246
#>
#> [[78]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1668 0.1920 -0.0725
#> [2,] 0.1920 0.2210 -0.0835
#> [3,] -0.0725 -0.0835 0.0315
#>
#>
#> [[79]]
#> [[79]][[1]]
#> x m y
#> x -0.9654 0.3400 -0.2761
#> m 1.6497 -0.8338 -0.5047
#> y -0.3753 0.3957 -0.3499
#>
#> [[79]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4109 -0.4424 -0.4244
#> [2,] -0.4424 0.6746 0.4574
#> [3,] -0.4244 0.4574 0.4383
#>
#>
#> [[80]]
#> [[80]][[1]]
#> x m y
#> x -0.3026 -0.2047 0.0103
#> m 0.7055 -0.9353 -0.6513
#> y -0.2565 0.7110 -0.5678
#>
#> [[80]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.9495 -0.5654 0.2685
#> [2,] -0.5654 0.5518 0.0761
#> [3,] 0.2685 0.0761 0.3347
#>
#>
#> [[81]]
#> [[81]][[1]]
#> x m y
#> x -0.4775 -0.6702 -0.3674
#> m 0.6551 -1.1234 0.4847
#> y -0.4049 0.6701 -0.7851
#>
#> [[81]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1560 -0.1204 -0.3361
#> [2,] -0.1204 0.0929 0.2594
#> [3,] -0.3361 0.2594 0.7243
#>
#>
#> [[82]]
#> [[82]][[1]]
#> x m y
#> x -0.8997 0.1674 -0.0816
#> m 0.0371 -0.7317 -0.0569
#> y -0.3321 0.9109 -0.6667
#>
#> [[82]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3845 0.2797 -0.0336
#> [2,] 0.2797 0.3338 0.1989
#> [3,] -0.0336 0.1989 0.3856
#>
#>
#> [[83]]
#> [[83]][[1]]
#> x m y
#> x -0.1421 -0.1995 0.1394
#> m 0.9687 -0.3008 0.1489
#> y -0.6430 1.1407 -0.8898
#>
#> [[83]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1318 -0.0655 -0.0658
#> [2,] -0.0655 0.8798 0.1607
#> [3,] -0.0658 0.1607 0.1233
#>
#>
#> [[84]]
#> [[84]][[1]]
#> x m y
#> x -0.3852 -0.0315 0.2066
#> m 0.9687 -0.3978 -0.2098
#> y -1.1187 0.8381 -0.6674
#>
#> [[84]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3246 -0.2849 0.0603
#> [2,] -0.2849 0.3160 0.0328
#> [3,] 0.0603 0.0328 0.1225
#>
#>
#> [[85]]
#> [[85]][[1]]
#> x m y
#> x -1.0925 0.0420 0.4191
#> m 0.8308 -0.6494 -0.0108
#> y -0.2201 0.3032 -0.9491
#>
#> [[85]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4257 0.0134 -0.3028
#> [2,] 0.0134 0.0004 -0.0095
#> [3,] -0.3028 -0.0095 0.2154
#>
#>
#> [[86]]
#> [[86]][[1]]
#> x m y
#> x -0.5568 -0.1659 -0.4839
#> m 0.5665 -0.7612 -0.3270
#> y -0.6213 0.8655 -0.3879
#>
#> [[86]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0339 0.1125 0.0390
#> [2,] 0.1125 0.3731 0.1294
#> [3,] 0.0390 0.1294 0.0449
#>
#>
#> [[87]]
#> [[87]][[1]]
#> x m y
#> x -0.5987 -0.4909 0.0054
#> m 0.1809 -0.8659 -0.2070
#> y -0.7260 0.8523 -0.5673
#>
#> [[87]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2267 -0.1144 -0.3784
#> [2,] -0.1144 0.2820 0.2866
#> [3,] -0.3784 0.2866 0.6725
#>
#>
#> [[88]]
#> [[88]][[1]]
#> x m y
#> x -0.7659 -0.1603 0.0522
#> m 0.4770 -0.3408 -0.3605
#> y -0.6887 0.9374 -0.6395
#>
#> [[88]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.1592 0.1971 0.2191
#> [2,] 0.1971 0.4384 0.4851
#> [3,] 0.2191 0.4851 0.5368
#>
#>
#> [[89]]
#> [[89]][[1]]
#> x m y
#> x -0.5778 -0.0748 0.0267
#> m 0.8781 -0.1231 0.3063
#> y -0.6204 0.5089 -0.8793
#>
#> [[89]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.0008 0.0072 -0.0189
#> [2,] 0.0072 0.0689 -0.1809
#> [3,] -0.0189 -0.1809 0.4748
#>
#>
#> [[90]]
#> [[90]][[1]]
#> x m y
#> x -0.1857 0.0988 0.2849
#> m 0.9520 -1.0198 0.0733
#> y -0.8156 0.6942 -1.1091
#>
#> [[90]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5997 -0.1292 0.1560
#> [2,] -0.1292 0.2586 -0.0034
#> [3,] 0.1560 -0.0034 0.5472
#>
#>
#> [[91]]
#> [[91]][[1]]
#> x m y
#> x -0.3640 -0.1348 0.1781
#> m 1.3082 -0.8654 -0.7101
#> y -0.8689 -0.1464 -0.7441
#>
#> [[91]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2796 -0.3091 -0.0428
#> [2,] -0.3091 0.3419 0.0474
#> [3,] -0.0428 0.0474 0.0066
#>
#>
#> [[92]]
#> [[92]][[1]]
#> x m y
#> x -0.0762 -0.0787 -0.2930
#> m 0.7552 -0.3781 -0.0594
#> y -0.5971 0.5933 -0.8808
#>
#> [[92]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5715 0.1102 0.5575
#> [2,] 0.1102 0.8148 -0.1461
#> [3,] 0.5575 -0.1461 0.6248
#>
#>
#> [[93]]
#> [[93]][[1]]
#> x m y
#> x -1.3732 -0.3970 0.0553
#> m 1.3340 -0.3115 0.0461
#> y -0.1439 0.6359 -0.5621
#>
#> [[93]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3154 0.3700 -0.0793
#> [2,] 0.3700 0.4711 0.0266
#> [3,] -0.0793 0.0266 0.4070
#>
#>
#> [[94]]
#> [[94]][[1]]
#> x m y
#> x -0.3704 -0.4275 0.1444
#> m 1.0074 -0.4072 0.0641
#> y -0.1719 0.6905 -1.0189
#>
#> [[94]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3796 -0.0664 -0.3805
#> [2,] -0.0664 0.0116 0.0666
#> [3,] -0.3805 0.0666 0.3815
#>
#>
#> [[95]]
#> [[95]][[1]]
#> x m y
#> x -0.3181 -0.0828 -0.1344
#> m 0.8139 -0.5644 -0.1238
#> y -0.3566 1.0848 -0.7158
#>
#> [[95]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3378 0.0921 0.0676
#> [2,] 0.0921 0.2749 -0.1716
#> [3,] 0.0676 -0.1716 0.1582
#>
#>
#> [[96]]
#> [[96]][[1]]
#> x m y
#> x -0.2664 -0.0638 0.0999
#> m 0.2656 -0.3639 -0.2983
#> y -0.8135 0.9058 -1.0199
#>
#> [[96]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3741 -0.0441 0.0745
#> [2,] -0.0441 0.1206 0.1639
#> [3,] 0.0745 0.1639 0.2732
#>
#>
#> [[97]]
#> [[97]][[1]]
#> x m y
#> x -0.6166 -0.1953 -0.0611
#> m 0.9496 -0.5474 0.1815
#> y -0.4707 0.6810 -0.2917
#>
#> [[97]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.5194 0.3316 0.0633
#> [2,] 0.3316 0.2116 0.0404
#> [3,] 0.0633 0.0404 0.0077
#>
#>
#> [[98]]
#> [[98]][[1]]
#> x m y
#> x -0.0497 -0.0940 0.2368
#> m 0.1232 -0.8687 0.3928
#> y -1.2069 0.5177 -0.9762
#>
#> [[98]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.2133 -0.2306 0.0941
#> [2,] -0.2306 0.2577 -0.1322
#> [3,] 0.0941 -0.1322 0.1518
#>
#>
#> [[99]]
#> [[99]][[1]]
#> x m y
#> x -0.7706 0.1325 -0.1804
#> m 0.8584 -0.7141 -0.1271
#> y -0.4257 0.9780 -0.3795
#>
#> [[99]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.4109 -0.3524 0.0863
#> [2,] -0.3524 0.3022 -0.0740
#> [3,] 0.0863 -0.0740 0.0181
#>
#>
#> [[100]]
#> [[100]][[1]]
#> x m y
#> x -0.2084 0.1132 0.0256
#> m 0.5607 -0.6442 -0.3224
#> y -0.1631 0.8814 -0.5928
#>
#> [[100]][[2]]
#> [,1] [,2] [,3]
#> [1,] 0.3654 -0.0459 0.0433
#> [2,] -0.0459 0.2185 0.0453
#> [3,] 0.0433 0.0453 0.0173
#>
#>