The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
TP <- TPmat(K)
Omega_true <- rOmega(TP)
class_0 <- sample(1:2^K, N, replace = L)
Alphas_0 <- matrix(0,N,K)
for(i in 1:N){
Alphas_0[i,] <- inv_bijectionvector(K,(class_0[i]-1))
}
Alphas <- sim_alphas(model="FOHM", Omega = Omega_true, N=N, L=L)
itempars_true <- matrix(runif(J*2,.1,.2), ncol=2)
Y_sim <- sim_hmcdm(model="DINA",Alphas,Q_matrix,Design_array,
itempars=itempars_true)
output_FOHM = hmcdm(Y_sim,Q_matrix,"DINA_FOHM",Design_array,100,30)
#> 0
output_FOHM
#>
#> Model: DINA_FOHM
#>
#> Sample Size: 350
#> Number of Items:
#> Number of Time Points:
#>
#> Chain Length: 100, burn-in: 50
summary(output_FOHM)
#>
#> Model: DINA_FOHM
#>
#> Item Parameters:
#> ss_EAP gs_EAP
#> 0.2268 0.1448
#> 0.1936 0.1967
#> 0.1645 0.2347
#> 0.1487 0.2092
#> 0.1489 0.1085
#> ... 45 more items
#>
#> Transition Parameters:
#> [1] 0.02241 0.03004 0.03006 0.02264 0.02932 0.02900 0.05417 0.06629 0.12017
#> [10] 0.17819 0.15945 0.02662 0.06635 0.10660 0.02111 0.03757
#> ... 15 more rows
#>
#> Class Probabilities:
#> pis_EAP
#> 0000 0.1670
#> 0001 0.2611
#> 0010 0.1588
#> 0011 0.2025
#> 0100 0.1458
#> ... 11 more classes
#>
#> Deviance Information Criterion (DIC): 18365.61
#>
#> Posterior Predictive P-value (PPP):
#> M1: 0.5084
#> M2: 0.49
#> total scores: 0.6293
a <- summary(output_FOHM)
head(a$ss_EAP)
#> [,1]
#> [1,] 0.2268467
#> [2,] 0.1936234
#> [3,] 0.1644741
#> [4,] 0.1487108
#> [5,] 0.1488766
#> [6,] 0.1347755
AAR_vec <- numeric(L)
for(t in 1:L){
AAR_vec[t] <- mean(Alphas[,,t]==a$Alphas_est[,,t])
}
AAR_vec
#> [1] 0.9450000 0.9450000 0.9685714 0.9850000 0.9878571
PAR_vec <- numeric(L)
for(t in 1:L){
PAR_vec[t] <- mean(rowSums((Alphas[,,t]-a$Alphas_est[,,t])^2)==0)
}
PAR_vec
#> [1] 0.7971429 0.8228571 0.8885714 0.9485714 0.9514286
a$DIC
#> Transition Response_Time Response Joint Total
#> D_bar 2154.499 NA 14475.25 1232.942 17862.69
#> D(theta_bar) 2054.542 NA 14122.52 1182.712 17359.77
#> DIC 2254.457 NA 14827.98 1283.172 18365.61
head(a$PPP_total_scores)
#> [,1] [,2] [,3] [,4] [,5]
#> [1,] 0.36 0.88 0.22 0.40 0.28
#> [2,] 0.74 0.78 0.88 1.00 0.92
#> [3,] 0.82 0.90 0.40 0.10 0.96
#> [4,] 0.50 0.72 0.02 0.82 0.58
#> [5,] 0.38 0.62 0.52 0.90 0.54
#> [6,] 0.32 1.00 1.00 0.82 0.80
head(a$PPP_item_means)
#> [1] 0.54 0.42 0.62 0.50 0.50 0.46
head(a$PPP_item_ORs)
#> [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [,14]
#> [1,] NA 0.88 0.54 0.50 0.76 0.88 0.76 0.62 0.28 0.56 0.20 0.64 0.08 0.24
#> [2,] NA NA 0.80 0.14 0.68 0.92 0.94 0.94 0.32 0.82 0.56 0.38 0.38 0.98
#> [3,] NA NA NA 0.34 0.36 0.28 0.54 0.36 0.72 0.50 0.58 0.68 1.00 0.76
#> [4,] NA NA NA NA 0.32 0.18 0.64 0.56 0.44 0.28 0.40 0.28 0.90 0.12
#> [5,] NA NA NA NA NA 0.44 0.64 0.68 0.36 0.40 0.42 0.30 0.78 0.34
#> [6,] NA NA NA NA NA NA 0.60 0.40 0.58 0.44 0.62 0.48 0.10 0.26
#> [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [,26]
#> [1,] 0.98 0.88 0.14 0.60 0.40 0.40 0.92 0.96 0.22 0.08 0.42 0.28
#> [2,] 0.44 0.74 0.40 0.52 0.56 0.52 0.32 0.60 0.92 0.18 0.34 0.08
#> [3,] 0.96 0.94 0.96 0.44 0.84 0.68 0.54 0.08 0.34 0.76 0.78 0.06
#> [4,] 0.88 0.40 0.20 0.20 0.02 0.74 0.38 0.52 0.64 0.88 1.00 0.04
#> [5,] 0.98 0.98 0.12 0.40 0.58 0.38 0.84 0.84 0.08 0.94 0.24 0.66
#> [6,] 0.84 0.78 0.12 0.34 0.18 0.30 0.96 0.78 0.62 0.82 0.42 0.44
#> [,27] [,28] [,29] [,30] [,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
#> [1,] 1.00 0.10 0.30 0.16 0.86 0.10 0.22 0.02 0.54 0.50 0.56 0.98
#> [2,] 0.68 0.72 0.18 0.26 0.00 0.10 0.32 0.52 0.12 0.64 0.48 0.32
#> [3,] 0.18 0.36 0.12 0.04 0.18 0.84 0.08 0.78 0.56 0.84 0.70 0.48
#> [4,] 0.64 0.78 0.92 0.74 0.92 0.80 0.38 0.42 0.98 0.98 0.86 0.72
#> [5,] 0.64 0.48 0.08 0.18 0.18 0.10 0.06 0.14 0.82 0.34 0.20 0.76
#> [6,] 0.60 0.56 0.60 0.06 0.06 0.44 0.24 0.00 0.58 0.36 0.00 0.62
#> [,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46] [,47] [,48] [,49] [,50]
#> [1,] 0.32 0.88 0.24 0.44 0.74 0.78 0.02 1.00 0.22 0.76 0.50 0.22
#> [2,] 0.96 0.12 0.10 0.94 1.00 0.28 0.06 0.66 0.56 0.66 0.28 0.44
#> [3,] 0.34 0.62 0.44 0.06 0.76 0.60 0.16 0.52 0.18 0.74 0.92 0.18
#> [4,] 0.66 0.88 0.02 0.60 0.32 0.72 0.54 0.14 0.02 0.12 0.92 0.02
#> [5,] 0.20 0.72 0.10 0.60 0.86 0.40 0.22 0.34 0.20 0.88 0.14 0.36
#> [6,] 0.42 0.14 0.18 0.52 0.56 0.44 0.28 0.70 0.36 0.54 0.74 0.00
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.