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Logistic regression versus XGBoost for detecting burned areas using satellite images
(Springer, 2024)
Artículo / Artikulua,
Classical statistical methods prove advantageous for small datasets, whereas machine learning algorithms can excel with larger datasets. Our paper challenges this conventional wisdom by addressing a highly significant ...
Pinus spp. somatic embryo conversion under high temperature: effect on the morphological and physiological characteristics of plantlets
(MDPI, 2020)
info:eu-repo/semantics/article,
Climatic variations in the current environmental scenario require plants with tolerance to sudden changes in temperature and a decrease in water availability. Accordingly, this tolerance will enable successful plantations ...
Small area estimation of gender-based violence: rape incidence risks in Uttar Pradesh, India
(Society of Statistics, Computer and Applications, 2018)
info:eu-repo/semantics/article,
Violence against women is considered an endemic problem in communities and countries
around the world, and it has been declared an issue of epidemic proportions by the World Health
Organization (WHO). In India, where the ...
Alleviating confounding in spatio-temporal areal models with an application on crimes against women in India
(SAGE Publications, 2021)
Artículo / Artikulua,
Assessing associations between a response of interest and a set of covariates in spatial areal models is the leitmotiv of ecological regression. However, the presence of spatially correlated random effects can mask or even ...
On the performances of trend and change-point detection methods for remote sensing data
(MDPI, 2020)
info:eu-repo/semantics/article,
Detecting change-points and trends are common tasks in the analysis of remote sensing data. Over the years, many different methods have been proposed for those purposes, including (modified) Mann-Kendall and Cox-Stuart ...
Bayesian inference in multivariate spatio-temporal areal models using INLA: analysis of gender-based violence in small areas
(Springer, 2020)
info:eu-repo/semantics/article,
Multivariate models for spatial count data are currently receiving attention in disease mapping to model two or more diseases jointly. They have been thoroughly studied from a theoretical point of view, but their use in ...
Space-time interactions in bayesian disease mapping with recent tools: making things easier for practitioners
(Edward Arnold, 2022)
Artículo / Artikulua,
Spatio-temporal disease mapping studies the distribution of mortality or incidence risks in space and its evolution in time, and it usually relies on fitting hierarchical Poisson mixed models. These models are complex for ...
Checking unimodality using isotonic regression: an application to breast cancer mortality rates
(Springer, 2016)
info:eu-repo/semantics/article,
In some diseases it is well-known that a unimodal mortality pattern exists. A clear example in developed countries is breast cancer, where mortality increased sharply until the nineties and then decreased. This clear ...
Filling missing data and smoothing altered data in satellite imagery with a spatial functional procedure
(Springer, 2019)
info:eu-repo/semantics/article,
Outliers and missing data are commonly found in satellite imagery. These are usually caused by atmospheric or electronic failures, hampering the correct monitoring of remote-sensing data. To avoid distorted data, we propose ...
Two-level resolution of relative risk of dengue disease in a hyperendemic city of Colombia
(Public Library of Science, 2018)
info:eu-repo/semantics/article,
Risk maps of dengue disease offer to the public health officers a tool to model disease risk in space and time. We analyzed the geographical distribution of relative incidence risk of dengue disease in a high incidence ...