Taconet_2023_statistical_models.zip

This file is part of "Data and code for: Physiological and behavioural resistance of malaria vectors in rural West-Africa: a data mining study to adress their fine-scale spatiotemporal heterogeneity, drivers, and predictability".

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File Citation
Taconet, Paul; Soma, Diloma Dieudonné; Zogo, Barnabas; Mouline, Karine; Simard, Frédéric; Koffi Amanan, Alphonsine; Dabiré, Roch Kounbobr; Pennetier, Cédric; Moiroux, Nicolas, 2023, "Data and code for: Physiological and behavioural resistance of malaria vectors in rural West-Africa: a data mining study to adress their fine-scale spatiotemporal heterogeneity, drivers, and predictability", https://doi.org/10.23708/LV8GEW, DataSuds, V5; Taconet_2023_statistical_models.zip [fileName]
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Dataset Citation
Taconet, Paul; Soma, Diloma Dieudonné; Zogo, Barnabas; Mouline, Karine; Simard, Frédéric; Koffi Amanan, Alphonsine; Dabiré, Roch Kounbobr; Pennetier, Cédric; Moiroux, Nicolas, 2023, "Data and code for: Physiological and behavioural resistance of malaria vectors in rural West-Africa: a data mining study to adress their fine-scale spatiotemporal heterogeneity, drivers, and predictability", https://doi.org/10.23708/LV8GEW, DataSuds, V5
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Data
MD5 a4094d27d5c9763ca3a8b7701dd71d84
Deposit Date 2023-05-24
Metadata Release Date 2023-05-26
Publication Date 2023-05-26
Size 149.0 MB
Type ZIP Archive
File Path Taconet_2023_data mining_malaria_vectors_West-Africa/
Description Folder containing the models : because the models may take very long to fit (due to the size of the raw data), they were pre-fit and saved as RDS files in this folder. To reduce computation time, users may open them directly from this folder instead of re-fitting them. NB : This archive needs to be unzipped before using the R script.
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R script (Taconet_2023_R_script_data_analysis.R) is licensed under the GNU General Public License v3.0.
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