Results 31 to 40 of about 280,435 (260)
Generalized Additive Models for Predicting Sea Level Rise in Coastal Florida
Geosciences, 2023 Within the last century, the global sea level has risen between 16 and 21 cm and will likely accelerate into the future. Projections from the Intergovernmental Panel on Climate Change (IPCC) show the global mean sea level (GMSL) rise may increase to up ...
Hanna N. Vaidya +4 more
doaj +1 more source
Generalized Additive Models with Unknown Link Function Including Variable Selection [PDF]
, 2013 The generalized additive model is a well established and strong tool that allows to model smooth effects of predictors on the response. However, if the link function, which is typically chosen as the canonical link, is misspecified, substantial bias is ...
Petry, Sebastian, Tutz, Gerhard
core +1 more source
Wildfires Impact Assessment on PM Levels Using Generalized Additive Mixed Models
Atmosphere, 2023 Wildfires are relevant sources of PM emissions and can have an important impact on air pollution and human health. In this study, we examine the impact of wildfire PM emissions on the Piemonte (Italy) air quality regional monitoring network using a ...
Gianluca Leone +6 more
doaj +1 more source
PEMODELAN PRODUKTIVITAS PADI DENGAN MENGGUNAKAN GENERALIZED ADDITIVE MODELS DI PROVINSI BANTEN
Jurnal Lebesgue, 2020 Tujuan dari penelitian ini adalah untuk melakukan pemodelan produktivitas padi. Sumber data yang digunakan dalam penelitian ini adalah data produktivitas padi, penggunaan pupuk, penggunaan benih, sistem tanam, serangan OPT, dampak perubahan iklim, dan ...
Wahyudi Manurung, Muhammad Fajar, Noviar
doaj +1 more source
Maximal Associated Regression: A Nonlinear Extension to Least Angle Regression
IEEE Access, 2021 This paper proposes Maximal Associated Regression (MAR), a novel algorithm that performs forward stage-wise regression by applying nonlinear transformations to fit predictor covariates.
Sanush K. Abeysekera +3 more
doaj +1 more source
Regularization for Generalized Additive Mixed Models by Likelihood-Based Boosting [PDF]
, 2011 With the emergence of semi- and nonparametric regression the generalized linear mixed model has been expanded to account for additive predictors. In the present paper an approach to variable selection is proposed that works for generalized additive mixed
Groll, Andreas, Tutz, Gerhard
core +2 more sources
Generalized additive modelling with implicit variable selection by likelihood based boosting [PDF]
, 2004 The use of generalized additive models in statistical data analysis suffers from the restriction to few explanatory variables and the problems of selection of smoothing parameters.
Binder, Harald, Tutz, Gerhard
core +2 more sources
BMC Medical Research Methodology, 2017 Background The analysis of correlated binary data is commonly addressed through the use of conditional models with random effects included in the systematic component as opposed to generalized estimating equations (GEE) models that addressed the random ...
Jie Pu, Di Fang, Jeffrey R. Wilson
doaj +1 more source
Markov-switching generalized additive models
, 2015 We consider Markov-switching regression models, i.e. models for time series regression analyses where the functional relationship between covariates and response is subject to regime switching controlled by an unobservable Markov chain.
Glennie, Richard +3 more
core +1 more source
BayesX: Analyzing Bayesian Structural Additive Regression Models
Journal of Statistical Software, 2005 There has been much recent interest in Bayesian inference for generalized additive and related models. The increasing popularity of Bayesian methods for these and other model classes is mainly caused by the introduction of Markov chain Monte Carlo (MCMC)
Andreas Brezger +2 more
doaj +1 more source