Table 1.
Measures of model estimation accuracy, smoothing strength, and variance quality for the simulated Poisson assumption data, simulated uniform assumption data, and real HIV data.
| Method | MSE | LCCC | MAD | G |
|---|---|---|---|---|
| Poisson Simulation | ||||
| Observed | 1.00E-05 | 0.214 | ||
| Poisson kriging | 1.47E-06 | 0.550 | 0.938 | 0.669 |
| UMBME | 4.83E-06 | 0.396 | 1.33 | 0.798 |
| Uniform Simulation | ||||
| Observed | 1.52E-06 | 0.618 | ||
| Poisson kriging | 1.15E-06 | 0.555 | 0.510 | 0.670 |
| UMBME | 6.43E-07 | 0.794 | 0.701 | 0.781 |
| HIV Data | ||||
| Observed | 1.87E-04 | 0.013 | ||
| Poisson kriging | 1.80E-04 | 0.039 | 0.00297 | |
| UMBME | 1.79E-04 | 0.040 | 0.00369 |
The MSE and LCCC for the simulated data describe divergence between the model estimated and true latent rate values. For the HIV data, the MSE and LCCC values describe divergence between the model cross-validation results and observed rate values. Bolded values represent the model with the greatest estimation accuracy (MSE, LCCC), greatest smoothing strength (MAD), or best fit variance (G) in each dataset.