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Federated generalized additive models for location, scale and shape [PDF]
BMC Medical Research MethodologyBackground The generalized additive model for location, scale and shape (GAMLSS) is a flexible regression model with a wide range of applications. In particular, it is the standard method to estimate age-specific percentile curves for clinical parameters
Annika Swenne +3 more
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Spatial modeling of HIV prevalence in Malawi using generalized additive models [PDF]
Frontiers in EpidemiologyIntroductionMalawi has made substantial progress in HIV prevention and treatment, yet HIV prevalence remains unevenly distributed across the country. Sub-national estimates are needed to guide targeted interventions.MethodsWe analyzed individual-level ...
Zacharie Tsala Dimbuene +6 more
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Hierarchical generalized additive models in ecology: an introduction with mgcv [PDF]
PeerJ, 2019 In this paper, we discuss an extension to two popular approaches to modeling complex structures in ecological data: the generalized additive model (GAM) and the hierarchical model (HGLM).
Eric J. Pedersen +3 more
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Meta-analysis of generalized additive models in neuroimaging studies
NeuroImage, 2021 Analyzing data from multiple neuroimaging studies has great potential in terms of increasing statistical power, enabling detection of effects of smaller magnitude than would be possible when analyzing each study separately and also allowing to ...
Øystein Sørensen +9 more
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Semina: Ciências Exatas e Tecnológicas, 2021 Generalized additive models for location, scale and shape (GAMLSS) are a very flexible statistical modeling framework, being an important generalization of the well-known generalized linear models and generalized additive models.
Fernanda V. Roquim +5 more
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Mapping spatial patterns of plant species based on machine-learning and regression models [PDF]
Desert, 2022 Various statistical techniques have been used for species distribution modeling that attempt to predict the occurrence of a given species with respect to environmental conditions.
H. Keshtkar, P. Pourmohammad
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Analyzing Temporal Trends of Urban Evaporation Using Generalized Additive Models
Land, 2022 This study aimed to gain new insights into urban hydrological balance (in particular, the evaporation from paved surfaces). Hourly evaporation data were obtained simultaneously from two high-resolution weighable lysimeters.
Basem Aljoumani +4 more
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evgam: An R Package for Generalized Additive Extreme Value Models
Journal of Statistical Software, 2022 This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions.
Benjamin D. Youngman
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Mathematics, 2023 Generalized Linear Models (GLMs) are the standard tool used for pricing in the field of automobile insurance. Generalized Additive Models (GAMs) are more complex and computationally intensive but allow taking into account nonlinear effects without the ...
Zuleyka Díaz Martínez +2 more
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Application of Machine Learning Techniques to High-Dimensional Clinical Data to Forecast Postoperative Complications. [PDF]
PLoS ONE, 2016 OBJECTIVE:To compare performance of risk prediction models for forecasting postoperative sepsis and acute kidney injury. DESIGN:Retrospective single center cohort study of adult surgical patients admitted between 2000 and 2010.
Paul Thottakkara +6 more
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