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The predictive power of the model and test sets in the whol..:
Weerapong Thanapongtharm (118229)
;
Sarin Suwanpakdee (119683)
;
Arun Chumkaeo (11778329)
..
https://figshare.com/articles/figure/The_predictive_power_of_the_model_and_test_sets_in_the_whole_modeling_period_/17107724. , 2021
Link:
https://doi.org/10.1371/journal.pntd.0009980.g003
RT Journal T1
The predictive power of the model and test sets in the whole modeling period
UL https://suche.suub.uni-bremen.de/peid=base-ftsmithonian:oai:figshare.com:article_17107724&Exemplar=1&LAN=DE A1 Weerapong Thanapongtharm (118229) A1 Sarin Suwanpakdee (119683) A1 Arun Chumkaeo (11778329) A1 Marius Gilbert (118241) A1 Anuwat Wiratsudakul (119668) YR 2021 K1 Ecology K1 Science Policy K1 Infectious Diseases K1 Virology K1 Environmental Sciences not elsewhere classified K1 Biological Sciences not elsewhere classified K1 study thus aimed K1 past four decades K1 last ten years K1 explainable variables using K1 cattle population density K1 generalized additive models K1 monthly rabies occurrences K1 spatial risk areas K1 cases gradually increased K1 identified risk factors K1 animal rabies cases K1 spatial models K1 risk factors K1 risk areas K1 rabies occurrences K1 animal rabies K1 slightly increased K1 gradually declined K1 rabies spread K1 xlink "> K1 temporal history K1 surveillance system K1 strategic plans K1 secondary roads K1 rigorously considered K1 results indicate K1 predictive maps K1 highly distributed K1 animals affected JF https://figshare.com/articles/figure/The_predictive_power_of_the_model_and_test_sets_in_the_whole_modeling_period_/17107724 LK http://dx.doi.org/https://doi.org/10.1371/journal.pntd.0009980.g003 DO https://doi.org/10.1371/journal.pntd.0009980.g003 SF ELIB - SuUB Bremen
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