Ordinales Modell

Modellübersicht

##  Family: cumulative 
##   Links: mu = probit; disc = log 
## Formula: stfdem ~ 1 + (1 | nuts2) 
##          disc ~ 1 + (1 | nuts2)
##    Data: cee04 (Number of observations: 7303) 
##   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)          0.48      0.16     0.24     0.85 1.00    24301    31790
## sd(disc_Intercept)     0.04      0.02     0.01     0.07 1.00    35293    34609
## 
## Population-Level Effects: 
##                Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept[1]      -3.18      0.90    -5.22    -1.71 1.00    22489    29885
## Intercept[2]      -2.46      0.70    -4.03    -1.32 1.00    22495    29661
## Intercept[3]      -1.59      0.46    -2.62    -0.84 1.00    22553    29583
## Intercept[4]      -0.66      0.22    -1.16    -0.32 1.00    23597    31315
## Intercept[5]       0.18      0.12    -0.02     0.44 1.00    29451    35832
## Intercept[6]       1.50      0.44     0.80     2.50 1.00    22917    30585
## Intercept[7]       2.35      0.67     1.27     3.87 1.00    22741    30530
## Intercept[8]       3.35      0.95     1.81     5.50 1.00    22676    30458
## Intercept[9]       4.47      1.26     2.41     7.32 1.00    22628    30187
## Intercept[10]      5.53      1.56     2.99     9.06 1.00    22574    30639
## disc_Intercept    -0.81      0.28    -1.34    -0.24 1.00    22470    30276
## 
## 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: stfdem ~ 1 
##          disc ~ 1
##    Data: cee04 (Number of observations: 7303) 
##   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]      -2.96      0.85    -4.88    -1.57 1.00    11326    13162
## Intercept[2]      -2.29      0.66    -3.78    -1.21 1.00    11385    13040
## Intercept[3]      -1.49      0.43    -2.45    -0.78 1.00    11385    13476
## Intercept[4]      -0.63      0.18    -1.05    -0.33 1.00    11598    14207
## Intercept[5]       0.15      0.05     0.06     0.27 1.00    15999    21304
## Intercept[6]       1.38      0.39     0.73     2.27 1.00    11374    13358
## Intercept[7]       2.16      0.62     1.14     3.56 1.00    11372    13210
## Intercept[8]       3.08      0.88     1.63     5.08 1.00    11339    13359
## Intercept[9]       4.11      1.18     2.18     6.78 1.00    11354    13508
## Intercept[10]      5.10      1.46     2.70     8.41 1.00    11306    13457
## disc_Intercept    -0.76      0.29    -1.30    -0.16 1.00    11323    13212
## 
## 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: stfdem ~ 1 + (1 | nuts2) 
##          sigma ~ 1 + (1 | nuts2)
##    Data: cee04 (Number of observations: 7303) 
##   Draws: 3 chains, each with iter = 66000; warmup = 6000; thin = 6;
##          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)           0.48      0.08     0.35     0.66 1.00    26335    28316
## sd(sigma_Intercept)     0.02      0.01     0.00     0.05 1.00    27927    27693
## 
## Population-Level Effects: 
##                 Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## Intercept           4.12      0.10     3.93     4.32 1.00    23979    27916
## sigma_Intercept     0.84      0.01     0.82     0.86 1.00    30122    28466
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   179.09     53.57    96.45   303.09 1.00    30005    28857
## 
## 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: stfdem ~ 1 
##          sigma ~ 1
##    Data: cee04 (Number of observations: 7303) 
##   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           4.15      0.03     4.10     4.21 1.00    23114    18223
## sigma_Intercept     0.86      0.01     0.84     0.87 1.00    22323    19281
## 
## Family Specific Parameters: 
##    Estimate Est.Error l-95% CI u-95% CI Rhat Bulk_ESS Tail_ESS
## nu   190.84     55.47   104.55   318.54 1.00    19928    17559
## 
## 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).