Results 1 to 10 of about 279,034 (281)

Data-driven estimation of the hydrologic response using generalized additive models [PDF]

Geoscientific Model Development
Estimating the hydrologic response of watersheds to precipitation events is key to understanding streamflow generation processes. Impulse Response Functions, commonly referred to as the Instantaneous Unit Hydrograph (IUH) in hydrology, have been used for
Q. Duchemin, M. G. Zanoni, M. G. Floriancic, M. G. Floriancic, H. Seybold, G. Obozinski, J. W. Kirchner, J. W. Kirchner, J. W. Kirchner, P. Benettin   +9 more
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Machine learning methods for empirical streamflow simulation: a comparison of model accuracy, interpretability, and uncertainty in seasonal watersheds [PDF]

Hydrology and Earth System Sciences, 2016
In the past decade, machine learning methods for empirical rainfall–runoff modeling have seen extensive development and been proposed as a useful complement to physical hydrologic models, particularly in basins where data to support process-based ...
J. E. Shortridge, S. D. Guikema, B. F. Zaitchik   +2 more
doaj   +1 more source

Smooth backfitting in generalized additive models

, 2007
Generalized additive models have been popular among statisticians and data analysts in multivariate nonparametric regression with non-Gaussian responses including binary and count data.
Mammen, Enno, Park, Byeong U., Yu, Kyusang   +2 more
core   +2 more sources

Predicting spatial variations in annual average outdoor ultrafine particle concentrations in Montreal and Toronto, Canada: Integrating land use regression and deep learning models

Environment International, 2023
Background: Concentrations of outdoor ultrafine particles (UFP;
Marshall Lloyd, Arman Ganji, Junshi Xu, Alessya Venuta, Leora Simon, Mingqian Zhang, Milad Saeedi, Shoma Yamanouchi, Joshua Apte, Kris Hong, Marianne Hatzopoulou, Scott Weichenthal   +11 more
doaj   +1 more source

Modelling trends in OH radical concentrations using generalized additive models [PDF]

Atmospheric Chemistry and Physics, 2009
During the TORCH campaign a zero dimensional box model based on the Master Chemical Mechanism was used to model concentrations of OH radicals. The model provided a close overall fit to measured concentrations but with some significant deviations. In this
L. S. Jackson, N. Carslaw, D. C. Carslaw, K. M. Emmerson   +3 more
doaj  

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Annals of Forest Science, 2023
Key message The non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were applied for the first time in crown width (CW) additive models of larch (Larix gmelinii Rupr.), birch (Betula platyphylla ...
Junjie Wang, Lichun Jiang, Shidong Xin, Youzhu Wang, Pei He, Yunfei Yan   +5 more
doaj   +1 more source

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, Octavio Cordova-Arevalo, Elena Rivo-Lopez   +2 more
doaj   +1 more source

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 ...
Brezger, Andreas, Lang, S.
core   +3 more sources

Quantile Generalized Additive Model a Robust Alternative to Generalized Additive Model

International Journal of Mathematical Research, 2021
Nonparametric regression is an approach used when the structure of the relationship between the response and the predictor variable is unknown. It tries to estimate the structure of this relationship since there is no predetermined form. The generalized additive model (GAM) and quantile generalized additive (QGAM) model provides an attractive framework
openaire   +2 more sources

Online Generalized Additive Model

, 2021
Additive models and generalized additive models are effective semiparametric tools for multidimensional data. In this article we propose an online smoothing backfitting method for generalized additive models with local polynomial smoothers. The main idea is to use a second order expansion to approximate the nonlinear integral equations to maximize the ...
Yang, Ying, Yao, Fang
openaire   +2 more sources