Report for: Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach

Title	Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach
Published in	Revista de Matemática: Teoría y Aplicaciones, December 2019
DOI	10.15517/rmta.v27i1.39931
Authors	Paola Vásquez, Antonio Loría, Fabio Sánchez, Luis A. Barboza

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.

Country	Count	As %
United States	1	100%

Type	Count	As %
Scientists	1	100%

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Country	Count	As %
Unknown	24	100%

Readers by professional status	Count	As %
Researcher	5	21%
Student > Bachelor	2	8%
Student > Ph. D. Student	2	8%
Student > Master	2	8%
Professor	1	4%
Other	2	8%
Unknown	10	42%

Readers by discipline	Count	As %
Agricultural and Biological Sciences	4	17%
Environmental Science	2	8%
Mathematics	2	8%
Earth and Planetary Sciences	2	8%
Computer Science	1	4%
Other	2	8%
Unknown	11	46%

Climate-driven statistical models as effective predictors of local dengue incidence in costa rica: a generalized additive model and random forest approach