Coerce an Object of Class simculta to a Matrix
Source: R/manCULTA-method-simculta.R
as.matrix.simculta.RdCoerce an Object of Class simculta to a Matrix
Usage
# S3 method for class 'simculta'
as.matrix(x, ...)Examples
x <- GenCULTA2Profiles(
n = 10,
m = 6,
common_trait_loading = matrix(
data = c(1, 1.25, 1.50, 1.75),
ncol = 1
),
common_state_loading = matrix(
data = c(1, 1.5, 1.75, 2.00),
ncol = 1
),
mu_t = NULL,
psi_t = NULL,
mu_p = NULL,
psi_p = NULL,
theta = diag(4),
mu_profile = cbind(
c(-3, -3, -3, -3),
c(3, 3, 3, 3)
),
mu_x = 0,
sigma_x = 1,
nu_0 = -3.563,
kappa_0 = 0.122,
alpha_0 = -3.586,
beta_00 = 2.250,
gamma_00 = 0.063,
gamma_10 = 0.094,
phi_0 = 0.311,
phi_1 = 0,
psi_s0 = 0.151,
psi_s = 0.290
)
as.matrix(x)
#> id covariate y1t0 y2t0 y3t0 y4t0 y1t1 y2t1
#> 1 1 -1.983009479 1.935365 3.745871 1.364566 1.701855 4.18332854 2.747512
#> 2 2 -0.219599804 2.879605 4.366086 5.053028 6.920815 4.48101918 4.580698
#> 3 3 1.045275869 5.196590 5.681926 6.825355 5.377838 4.72846546 3.907936
#> 4 4 1.877329566 2.881662 3.584416 1.225822 1.720035 -1.84670951 -2.854165
#> 5 5 0.002606196 3.516095 3.597233 1.393627 1.166944 2.45575263 5.557888
#> 6 6 -0.080669935 1.635176 1.894422 3.355718 5.707425 3.46023526 1.162914
#> 7 7 0.962982281 6.651101 4.604233 6.453623 7.990556 5.84199343 4.252758
#> 8 8 0.053571017 1.448337 2.409726 6.369498 8.244134 3.38787170 5.433822
#> 9 9 -0.434898409 1.229037 1.633926 1.710707 1.918163 0.07559754 1.466063
#> 10 10 -1.737297255 4.117725 1.879963 3.461637 1.585253 5.58562177 3.524630
#> y3t1 y4t1 y1t2 y2t2 y3t2 y4t2 y1t3
#> 1 3.2068428 0.8113813 0.9095797 2.608498 -0.08069906 -0.1582283 2.0764357
#> 2 6.1054445 8.0362324 3.7619039 4.228701 5.29879749 8.7945633 3.7541588
#> 3 5.1989012 4.7400166 4.6385099 6.018249 4.69365731 4.4609117 5.0611689
#> 4 -5.3870055 -3.0535510 -1.6701116 -3.070749 -4.50804314 -3.0060741 1.1130136
#> 5 3.3917156 1.7134325 1.7949735 4.802798 3.65713816 2.4544106 3.7535511
#> 6 5.7435932 4.7142935 3.6178408 1.588543 3.97641606 4.7527450 3.2745581
#> 7 2.8602632 4.9794176 4.8495430 4.651606 5.91707893 5.7834760 2.3197027
#> 8 5.1538669 5.2480044 2.0879810 4.101336 5.08700005 4.7423719 4.0563619
#> 9 0.7626519 -0.7897040 2.1754039 -0.199107 -3.09467379 -2.4757455 0.1606699
#> 10 1.4043232 2.9540545 4.0969394 4.333582 3.29546224 5.3292428 6.3439956
#> y2t3 y3t3 y4t3 y1t4 y2t4 y3t4 y4t4
#> 1 4.4329359 3.0900213 1.876820 1.050714 3.6581381 2.0643827 0.1759829
#> 2 6.1406923 5.5989344 10.265874 3.291692 5.1757668 4.1114430 5.1965724
#> 3 4.8043162 5.8033974 2.234707 4.031673 3.3761597 4.4950492 3.9296157
#> 4 2.5333886 0.9816833 1.155072 3.114503 2.5158551 -0.7750244 4.3878009
#> 5 6.4197792 3.5749083 2.620797 2.732721 2.6527038 2.8604171 0.4033026
#> 6 0.8063852 2.5786180 3.024870 -3.384522 -2.7439943 -1.5522302 -1.3149698
#> 7 3.1086343 3.0480726 3.571580 2.754967 5.3511826 6.7289042 4.4813255
#> 8 2.9880311 3.9097630 7.204085 1.295198 0.4752935 2.8023005 4.3122410
#> 9 1.3381695 -0.4119574 -1.082401 -1.259015 0.3888265 -1.3176131 -2.8530258
#> 10 6.0891161 2.9349986 3.318092 6.271778 2.9837199 4.4180837 2.9109767
#> y1t5 y2t5 y3t5 y4t5
#> 1 1.5798351 3.7510478 -0.09251369 0.7427856
#> 2 3.4528374 5.3010372 8.38104288 10.4120457
#> 3 5.3018227 3.9559178 5.18055614 3.8186870
#> 4 4.9510353 4.9660349 0.90628527 2.6536198
#> 5 0.8227236 5.3478833 1.36275577 -0.7789928
#> 6 2.3467674 -0.0083522 3.27710285 1.7446696
#> 7 5.1024621 6.7760830 7.97914621 6.6176736
#> 8 3.0621063 3.6710564 3.18474040 2.6530429
#> 9 -6.7593672 -6.0362433 -7.04019584 -6.1904019
#> 10 5.4792772 3.3074747 2.49676568 2.0490818