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VBORNET gap analysis: Sand fly vector distribution models utilised to identify areas of potential species distribution in areas lacking records Instituut voor Tropische Geneeskunde
This is the first of a number of planned data papers presenting modelled vector distributions, the models in this paper were produced during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. This data paper contains the sand fly model outputs produced as part of the VBORNET project. Further data papers will be published after sampling seasons when more field data will become ...
VBORNET gap analysis: Mosquito vector distribution models utilised to identify areas of potential species distribution in areas lacking records Instituut voor Tropische Geneeskunde
This is the second of a number of planned data papers presenting modelled vector distributions produced originally during the ECDC funded VBORNET project. This work continues under the VectorNet project now jointly funded by ECDC and EFSA. Further data papers will be published after sampling seasons when more field data will become available allowing further species to be modelled or validation and updates to existing models. The data package ...
Absence reduction in entomological surveillance data to improve niche-based distribution models for Culicoides imicola Universiteit Gent
The gradient function as an exploratory goodness-of-fit assessment of the random-effects distribution in mixed models Universiteit Hasselt KU Leuven
Inference in mixed models is often based on the marginal distribution obtained from integrating out random effects over a pre-specified, often parametric, distribution. In this paper, we present the so-called gradient function as a simple graphical exploratory diagnostic tool to assess whether the assumed random-effects distribution produces an adequate fit to the data, in terms of marginal likelihood. The method does not require any ...
Input variable selection with a simple genetic algorithm for conceptual species distribution models : a case study of river pollution in Ecuador Universiteit Gent
A critical analysis of performance criteria for the evaluation and optimisation of fuzzy models for species distribution Universiteit Gent
Uncertainty propagation in vegetation distribution models based on ensemble classifiers Universiteit Gent Universiteit Antwerpen
Ensemble learning techniques are increasingly applied for species and vegetation distribution modelling, often resulting in more accurate predictions. At the same time, uncertainty assessment of distribution models is gaining attention. In this study, Random Forests, an ensemble learning technique, is selected for vegetation distribution modelling based on environmental variables. The impact of two important sources of uncertainty, that is the ...