Results 31 to 40 of about 14,693,426 (258)
Just Another Gibbs Additive Modeler: Interfacing JAGS and mgcv
Journal of Statistical Software, 2016 The BUGS language offers a very flexible way of specifying complex statistical models for the purposes of Gibbs sampling, while its JAGS variant offers very convenient R integration via the rjags package.
Simon N. Wood
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Fisheries and Aquatic Sciences, 2020 Three generalized additive models were applied to the distribution of anchovy eggs and oceanographic factors to determine the occurrence of anchovy spawning grounds in Korean waters and to identify the indicators of their occurrence using ...
Jin Yeong Kim +2 more
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The Extent of Gender Gap in Citations in Ophthalmology Literature
Frontiers in Medicine, 2022 PurposeTo investigate the severity and causes of gender imbalance in the counts of ophthalmology citations.MethodsThe PubMed database was searched to identify cited papers that were published in four journals (Prog Retin Eye Res, Ophthalmology, JAMA ...
Suqi Cao +4 more
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Generalized structured additive regression based on Bayesian P-splines [PDF]
, 2003 Generalized additive models (GAM) for modelling nonlinear effects of continuous covariates are now well established tools for the applied statistician. In this paper we develop Bayesian GAM's and extensions to generalized structured additive regression ...
Lang, S., Brezger, Andreas, Lang, Stefan
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Mapping wind erosion hazard with regression-based machine learning algorithms
Scientific Reports, 2020 Land susceptibility to wind erosion hazard in Isfahan province, Iran, was mapped by testing 16 advanced regression-based machine learning methods: Robust linear regression (RLR), Cforest, Non-convex penalized quantile regression (NCPQR), Neural network ...
Hamid Gholami +3 more
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Using flexible regression models for calculating hospital’s production functions
BMC Health Services Research, 2020 Background The relative lack of flexibility of parametric models has led to the development of nonparametric regression techniques based on the family of generalized additive models. However, despite the potential advantages of using Generalized Additive
Francisco Reyes-Santías +2 more
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Information, 2021 Background and objectives: Machine learning approaches using random forest have been effectively used to provide decision support in health and medical informatics. This is especially true when predicting variables associated with Medicare reimbursements.
Shrirang A. Kulkarni +7 more
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Capitalization effects of rivers in urban housing submarkets – A case study of the Yangtze River
International Journal of Strategic Property ManagementThe study aims to investigate the heterogeneity of the Yangtze River’s impact on housing prices, using the data of 12,325 residential transactions within 8 kilometers of the Yangtze River in Wuhan, based on submarkets divided according to geographical ...
Xiaoling Ke +4 more
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Propriety of Posteriors in Structured Additive Regression Models: Theory and Empirical Evidence [PDF]
, 2006 Structured additive regression comprises many semiparametric regression models such as generalized additive (mixed) models, geoadditive models, and hazard regression models within a unified framework.
Kneib, Thomas, Fahrmeir, Ludwig
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Frontiers in Endocrinology, 2022 ObjectiveAccording to a recent study, serum total bile acids (TBA) may preserve lumbar bone mineral density (BMD) in Cushing syndrome patients, and BMD is directly linked to bone health.
Jingxin Liu, Yuxing Chen, Qi Luo
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