23/05/2024 11:30h Palestra IRSE/IPMA DivRP
Marta Rufino
Vimos por este meio anunciar ou relembrar, mais uma palestra no nosso ciclo de palestras do IRSE - IPMA-DivRP.
Link para o evento, titulo, resumo e biografia em baixo.
Para os participantes por zoom, é fundamental colocarem o vosso nome e instituição quando entrarem no zoom.
Até lá !
Marta, Ana e Pedro
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Dear colleagues,
We hereby announce or recall, another lecture in our cycle of IRSE - IPMA-DivRP lectures.
Link to event, title, abstract and biography below .
For zoom participants, it is essential to put your name and institution when you enter the zoom.
See you then !
SAVE THE DATE *** PALESTRA IRSE - DIVRP ***
Lugar: Online
Zoom:
Meeting ID: 914 0414 8973 / Password: 583275
23/05/2024 11:30h Palestra IRSE/IPMA DivRP
Name: Mario Figueira (University of Valencia)
Title: A shiny app for spatial modeling in Species Distribution Model
Abstract:
The fast evolution of Species Distribution Models (SDMs) in ecology has ushered in a need for sophisticated tools capable of handling the increasing complexity of data and model structures. In response, numerous tools have emerged, predominantly in the form of new R packages and Shiny applications. However, despite the popularity of the Integrated Nested Laplace Approximation (INLA) method within ecological sciences, its integration into user-friendly interfaces for spatial modeling has lagged behind.
Addressing this gap, we introduce BAYSPINS (BAYesian SPatial INla for SDMs), a novel application designed to harness the power of INLA in a user-friendly manner. Whether for novices seeking simplicity or experts craving efficiency, BAYSPINS offers a solution for conducting rapid initial analyses without the need for extensive coding.
BAYSPINS accommodates both geostatistical and preferential modeling, as well as a blend of the two approaches. By seamlessly integrating the intricate SPDE-FEM (Stochastic Partial Differential Equation, Finite Elements Method) technique, it enables continuous spatial analysis through an intuitive visual interface. Users can opt for default settings to streamline the process or fine-tune a plethora of parameters to tailor the modeling process to their specific needs.
In essence, BAYSPINS empowers users to swiftly evaluate data or delve into comprehensive studies, depending on their skill level and grasp of the underlying principles. With its accessible interface and powerful capabilities, BAYSPINS heralds a new era in the democratization of sophisticated ecological modeling tools.
Biografía:
PhD student at the University of Valencia, specializing in spatial and spatio-temporal statistics, involved in several research projects applying spatial analysis techniques. Contributions include analyzing the distribution of Fasciola Hepatica in Galicia and Ceratitis Capitata distribution in Valencia. Additionally, participating in a European project for spatio-temporal analysis of land use and a national project for developing Bayesian statistical methodologies, with a specific focus on methods for analyzing Big Data and compositional data.
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Portuguese Institute for the Sea and the Atmosphere (IPMA)
Centre of Statistics and its Applications (CEAUL)
Faculty of Sciences, Univ. of Lisbon, Portugal