Model run using Apollo for R, version 0.1.0 
www.ApolloChoiceModelling.com

Model name                       : Apollo_example_25_bayesian_burnin100k_estimation100k
Model description                : ICLV model on drug choice data, using continuous measurement model for indicators
Model run at                     : 2020-11-10 11:33:30
Estimation method                : Hierarchical Bayes
Number of individuals            : 1000
Number of observations           : 10000

Number of cores used             :  1 

Estimation carried out using RSGHB
Burn-in iterations               : 1e+05
Post burn-in iterations          : 1e+05
LL(start)                        : -17403.08
LL(0)                            : NA
Average post. LL post burn-in    : -16600.46
Average post. RLH post burn-in   : 0.1968


Chain convergence report (Geweke test)

Fixed (non random) parameters (t-test value for Geweke test)
      b_brand_Novum   b_brand_BestValue b_brand_Supermarket    b_brand_PainAway        b_country_CH        b_country_DK       b_country_IND       b_country_RUS       b_country_BRA         b_char_fast       b_char_double 
             5.5871             -1.0737             11.8088              3.1172              0.0308             -6.0026              0.9491             -1.8095              2.9799             -4.1786             -3.7462 
             b_risk             b_price              lambda      gamma_reg_user    gamma_university        gamma_age_50        zeta_quality     zeta_ingredient         zeta_patent      zeta_dominance          sigma_qual 
           -18.4842              1.0404             -1.0119             -1.9034             -2.0809             -4.7793             -5.9304             -1.9038              1.5934             -0.8102              2.6320 
         sigma_ingr          sigma_pate          sigma_domi 
            -0.4916             -2.0934              4.0146 

Random parameters (t-test value for Geweke test)
var1 
 NaN 

Covariances of random parameters (t-test value for Geweke test)
eta_eta 
    NaN 


Summary of parameter chains

Non-random coefficients 
                       Mean     SD
b_brand_Artemis      0.0000     NA
b_brand_Novum       -0.2696 0.0109
b_brand_BestValue   -0.5834 0.0103
b_brand_Supermarket -0.2802 0.0207
b_brand_PainAway    -1.1821 0.0413
b_country_CH         0.6922 0.0156
b_country_DK         0.3718 0.0243
b_country_USA        0.0000     NA
b_country_IND       -0.3508 0.0204
b_country_RUS       -0.8991 0.0144
b_country_BRA       -0.7233 0.0309
b_char_standard      0.0000     NA
b_char_fast          0.7654 0.0121
b_char_double        1.2138 0.0122
b_risk              -0.0016 0.0001
b_price             -0.7354 0.0176
lambda               0.6957 0.0103
gamma_reg_user      -0.7069 0.0209
gamma_university    -0.4060 0.0208
gamma_age_50         0.6903 0.0248
zeta_quality         0.5746 0.0132
zeta_ingredient     -0.4227 0.0157
zeta_patent          0.6530 0.0175
zeta_dominance      -0.4041 0.0138
sigma_qual           1.0786 0.0078
sigma_ingr           1.1509 0.0146
sigma_pate           1.0999 0.0134
sigma_domi           1.0783 0.0167

Upper level model results for mean parameters for underlying Normals 
    Mean SD
eta    0  0

Upper level model results for covariance matrix for underlying Normals (means across iterations) 
    eta
eta   1

Upper level model results for covariance matrix for underlying Normals (SD across iterations) 
    eta
eta   0

Summary of distributions of random coeffients (after distributional transforms) 
       Mean     SD
[1,] -8e-04 1.0019

Results for posterior means for random coefficients 
      [,1]   [,2]
eta 0.0602 0.7722

