Model | lnL |
k
| LRT | AIC | BIC | Bowker |
|---|
| | | | H | NH2 | NH3 | | | # tests | median |
|---|
H | -14110.628293 | 185 | | | | 28591.26 | 29380.69 | 0.0008 | 0.0028 |
NH1 | -13810.371502 | 368 | 600.51 | 556.74 | 416.97 |
28356.74
| 29927.07 | 0.7010 | 0.8110 |
NH2 | -14088.739682 | 189 | 43.78 | | | 28555.48 | 29361.98 | 0.0040 | 0.0141 |
NH3 | -14018.854234 | 191 | 183.55 | 139.77 | | 28419.71 |
29234.74
| 0.1448 | 0.2672 |
NH4 | -13970.841467 | 368 | 279.57 | | | 28677.68 | 30248.01 | 0.0015 | 0.0047 |
- Comparison of the various non-homogeneous models with the homogeneous case, using different criteria. k is the number of parameters and lnL is the log likelihood of each model. The Akaike's information criterion (AIC) of each model is defined as 2k - 2·lnL, and the lowest value, corresponding to the best model according to this criterion is in bold font. The Bayesian information criterion (BIC) is computed as k· ln(n) - 2·lnL, n = 527 being the number of observations. The lowest value is in bold font. The likelihood ratio test (LRT) allows to compare nested models only, and is defined as minus two times the logarithm of the ratio of likelihoods. All LRT are significant at the 0.1% level. This ratio follows a χ2 distribution with the number of additional parameters as the degrees of freedom. The last two columns show the p-values of the two Bowker's test introduced in this paper.
