Ordinales Modell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: stfeco ~ 1 + (1 | nuts2) 
##          disc ~ 1 + (1 | nuts2)
##    Data: cee04 (Number of observations: 7434) 
##   Draws: 3 chains, each with iter = 84000; warmup = 6000; thin = 6;
##          total post-warmup draws = 39000
## 
## Group-Level Effects: 
## ~nuts2 (Number of levels: 26) 
##                    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept)          0.38      0.13     0.19     0.69 1.00    25332    32951
## sd(disc_Intercept)     0.08      0.02     0.06     0.12 1.00    35820    37884
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -2.41      0.71    -4.04    -1.28 1.00    23519    31333
## Intercept[2]      -1.69      0.50    -2.83    -0.89 1.00    23575    31441
## Intercept[3]      -0.75      0.23    -1.29    -0.38 1.00    24141    31386
## Intercept[4]       0.22      0.11     0.05     0.47 1.00    30597    35934
## Intercept[5]       0.99      0.30     0.52     1.67 1.00    24470    31469
## Intercept[6]       2.15      0.62     1.14     3.57 1.00    23781    30837
## Intercept[7]       3.02      0.88     1.61     5.02 1.00    23699    30740
## Intercept[8]       3.95      1.14     2.11     6.56 1.00    23639    31076
## Intercept[9]       4.99      1.45     2.67     8.30 1.00    23583    30871
## Intercept[10]      5.68      1.65     3.04     9.45 1.00    23592    31048
## disc_Intercept    -0.67      0.29    -1.23    -0.09 1.00    23485    31089
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Ordinales Nullmodell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: stfeco ~ 1 
##          disc ~ 1
##    Data: cee04 (Number of observations: 7434) 
##   Draws: 3 chains, each with iter = 84000; warmup = 6000; thin = 6;
##          total post-warmup draws = 39000
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -2.24      0.65    -3.71    -1.17 1.00    14726    16779
## Intercept[2]      -1.57      0.46    -2.60    -0.82 1.00    14731    16848
## Intercept[3]      -0.69      0.20    -1.15    -0.36 1.00    14877    17341
## Intercept[4]       0.22      0.07     0.11     0.38 1.00    16721    20994
## Intercept[5]       0.93      0.27     0.49     1.55 1.00    14852    17187
## Intercept[6]       2.00      0.58     1.05     3.32 1.00    14761    16609
## Intercept[7]       2.80      0.82     1.47     4.64 1.00    14769    16701
## Intercept[8]       3.64      1.06     1.91     6.02 1.00    14752    16911
## Intercept[9]       4.57      1.33     2.40     7.56 1.00    14735    16731
## Intercept[10]      5.18      1.51     2.72     8.57 1.00    14730    16833
## disc_Intercept    -0.63      0.29    -1.17    -0.02 1.00    14722    16700
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Metrisches Modell

Modellübersicht

##  Family: student 
##   Links: mu = identity; sigma = log; nu = identity 
## Formula: stfeco ~ 1 + (1 | nuts2) 
##          sigma ~ 1 + (1 | nuts2)
##    Data: cee04 (Number of observations: 7434) 
##   Draws: 3 chains, each with iter = 33000; warmup = 3000; thin = 3;
##          total post-warmup draws = 30000
## 
## Group-Level Effects: 
## ~nuts2 (Number of levels: 26) 
##                     Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## sd(Intercept)           0.39      0.07     0.28     0.54 1.00    17212    25351
## sd(sigma_Intercept)     0.07      0.01     0.04     0.10 1.00    22877    28028
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           3.34      0.08     3.18     3.50 1.00    12677    20464
## sigma_Intercept     0.74      0.02     0.70     0.77 1.00    22230    26026
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   178.19     53.43    95.81   303.20 1.00    30678    28875
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Metrisches Nullmodell

Modellübersicht

##  Family: student 
##   Links: mu = identity; sigma = log; nu = identity 
## Formula: stfeco ~ 1 
##          sigma ~ 1
##    Data: cee04 (Number of observations: 7434) 
##   Draws: 3 chains, each with iter = 11500; warmup = 1500; thin = 1;
##          total post-warmup draws = 30000
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           3.34      0.03     3.29     3.39 1.00    20103    17702
## sigma_Intercept     0.76      0.01     0.75     0.78 1.00    22013    18124
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   177.13     52.60    96.33   298.11 1.00    20488    19350
## 
## Draws were sampled using sampling(NUTS). For each parameter, Bulk_ESS
## and Tail_ESS are effective sample size measures, and Rhat is the potential
## scale reduction factor on split chains (at convergence, Rhat = 1).

Trace-Plots

Trace-Plot

Autokorrelation-Plots

Autokorrelation-Plot

Posterior-Verteilung

Posterior-Plot

Copyright:
Benedikt Philipp Kleer, 2022 (Online-Appendix zur Promotion, eingereicht am 14. September 2022, Fachbereich 03, Justus-Liebig-Universität Gießen).