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 -0.434898409 3.782242 1.351715 2.9427369 1.7949214 4.7545013 2.2836476
#> 2 2 -1.737297255 2.153713 2.448050 6.4307622 0.8202692 0.8099121 4.1523962
#> 3 3 -1.263695600 3.187589 4.987633 6.4153168 6.5465086 3.1278372 1.3172155
#> 4 4 0.406308512 3.108124 3.289756 6.9083992 5.1656045 4.7647438 0.2918487
#> 5 5 -1.459653968 2.499432 3.046025 0.4712187 -2.3845844 3.5944713 3.8803803
#> 6 6 1.048457370 0.299359 4.619669 3.4303420 5.3557826 0.9536217 1.1252707
#> 7 7 -1.346430539 2.782637 4.554230 5.1525935 3.7179767 4.2753833 3.1269512
#> 8 8 -0.193570558 2.952590 4.102005 4.9740751 1.9156244 2.2832942 3.1343173
#> 9 9 -0.002335957 4.250033 1.626440 0.6906344 1.2766068 3.2450412 1.9506263
#> 10 10 -0.012829734 5.433353 3.812659 6.2252314 3.2612792 4.8918429 5.0229852
#> y3t1 y4t1 y1t2 y2t2 y3t2 y4t2 y1t3
#> 1 2.2800796 1.545085 3.6404985 2.0661432 2.46226309 3.3430296 6.261274
#> 2 4.6597573 1.445941 1.7945394 3.0821225 5.49946361 1.7598261 1.706360
#> 3 3.2713902 2.056381 3.8656836 5.3791597 5.28948442 4.4328089 3.912252
#> 4 1.8553591 3.742105 4.5223464 1.3612592 2.63381217 4.1658952 3.304857
#> 5 -0.1664978 2.529035 3.2937047 1.5898308 -0.06461959 0.5358452 4.090840
#> 6 3.1265891 1.472146 1.9770195 3.6907168 6.31785544 6.6038299 3.282751
#> 7 1.7793689 3.670097 2.0724988 3.4258927 2.00656735 4.0343981 4.055913
#> 8 3.7826602 1.057187 1.3915526 3.7066773 3.04693688 2.0324709 1.278664
#> 9 1.8041649 4.751561 1.1375511 -0.7129968 0.08363337 1.2912565 4.924558
#> 10 5.3178785 1.589557 -0.7770755 -1.3727677 -1.77426217 -1.9393138 7.155552
#> y2t3 y3t3 y4t3 y1t4 y2t4 y3t4 y4t4
#> 1 3.3773335 4.24495050 4.567762 2.597836 2.3624999 1.6390733 0.6512027
#> 2 2.5309273 4.74309474 1.061035 3.539222 3.6056807 5.4873518 0.8585451
#> 3 4.2702215 5.07898106 3.673591 -1.015005 0.5103997 -1.6658645 -1.2411368
#> 4 0.3935612 5.37047178 4.426303 1.096204 -0.7752972 2.3638727 3.5877719
#> 5 3.0764778 -0.07384367 -2.829576 3.947661 3.3552241 -0.4647369 -1.1693167
#> 6 2.4855965 3.30710884 5.360090 1.127334 5.0197537 4.0950866 3.8396742
#> 7 4.3559035 2.99335834 5.837571 4.052356 3.7017661 3.0428572 5.4234873
#> 8 4.7417310 3.74977382 2.752900 1.815274 2.0898185 3.7224588 2.4132507
#> 9 0.7214674 2.14612087 3.449438 2.518486 0.6776673 0.7536733 0.8825943
#> 10 5.6849615 6.10065068 3.670067 4.413898 7.8400176 7.6913321 5.6675081
#> y1t5 y2t5 y3t5 y4t5
#> 1 6.7140408 2.7358992 2.6179755 2.13149113
#> 2 0.1362200 1.9693966 1.9823002 -0.02665275
#> 3 -0.6500289 0.5742261 -0.8800453 -1.67944259
#> 4 4.7573703 0.3594832 1.5869248 3.75196861
#> 5 2.0335680 1.5504328 -0.2187459 -2.28358134
#> 6 0.8246693 2.3510496 2.3772615 2.91348036
#> 7 1.3492794 3.3772932 1.9984974 1.77056520
#> 8 4.4929101 5.3540349 2.0714714 1.31843979
#> 9 3.2608315 0.8333539 4.4592592 3.49847189
#> 10 4.7303793 4.3591860 4.5074282 4.50461219