Table 4 Advantages and disadvantages of logistic regression, boosted regression trees, cross-validated logistic regression and Maxent model
From: Modelling zoonotic diseases in humans: comparison of methods for hantavirus in Sweden
| Â | Advantages | Disadvantages |
|---|---|---|
Logistic regression | -Best goodness-of-fit and predictive power | -Need of real absence points |
-Inclusion of variables reflecting the surrounding environment | ||
BRT | -Account for non-linearity of biological processes | -Need of real absence points |
-Modelling of interactions | -Impossible to see all three at one time | |
-Inclusion of variables reflecting the surrounding environment | -Difficulty to extrapolate | |
CV method | -Available sites instead of absence sites | -Fastidious calculations |
-Inclusion of variables reflecting the surrounding environment | -Limited value compared to logistic regression | |
Maxent model | -Ease of use | -Complex estimators, difficulty to extrapolate |
-Spatially continuous results | -Need of spatially continuous data | |
-Accounts for non-linearity of biological processes | -Limited by the coarsest resolution and the smallest extent of variables |