R Under development (unstable) (2025-08-21 r88668 ucrt) -- "Unsuffered Consequences"
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> library(testthat)
> library(disaggregation)
> 
> test_check("disaggregation")
Fitting model. This may be slow.
The data contains 100 polygons and 400 pixels
The largest polygon contains 4 pixels and the smallest polygon contains 4 pixels
There are 2 covariates

Covariate summary:
     layer1           layer2      
 Min.   :-8.313   Min.   :-2.495  
 1st Qu.: 5.374   1st Qu.: 6.102  
 Median :10.651   Median :10.458  
 Mean   :10.397   Mean   :10.746  
 3rd Qu.:15.169   3rd Qu.:15.197  
 Max.   :24.671   Max.   :25.693  
They data contains 100 polygons and 400 pixels
The largest polygon contains 4 pixels and the smallest polygon contains 4 pixels
There are 2 covariates
Likelihood function: poisson 
Link function: log 
Model parameters:
                      Estimate Std. Error
intercept          3.978127956 0.30380529
layer1             0.010151343 0.01755424
layer2             0.029984700 0.01920462
iideffect_log_tau  0.002751583 0.14765218
log_sigma         -2.478663358 0.87831038
log_rho            2.802824638 0.85290269

Model convergence: 0 (relative convergence (4))
Negative log likelihood:  -415.028436198763 

In sample performance:
       RMSE       MAE   pearson spearman log_pearson
1 0.9884335 0.7571368 0.9999985        1   0.9989724
Bayesian disaggregation model result

Likelihood function: poisson 
Link function: log 

Parameter values:
        intercept            layer1            layer2 iideffect_log_tau 
      3.978127956       0.010151343       0.029984700       0.002751583 
        log_sigma           log_rho 
     -2.478663358       2.802824638 
Predction from disaggregation model

Components of the model: covariates field 

There are 100 uncertainty realisations

The mean predicted values range from 53.2 to 130 
The predicted IQR takes values from 32.9 to 163 
Predction from disaggregation model

Components of the model: covariates field 

There are 100 uncertainty realisations[ FAIL 0 | WARN 0 | SKIP 0 | PASS 299 ]
> 
> 
> proc.time()
   user  system elapsed 
 347.70    8.95  356.76