Results 1 to 10 of about 280,784 (278)
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
doaj +2 more sources
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
doaj +3 more sources
Linking watershed nutrient loading to estuary water quality with generalized additive models [PDF]
PeerJ, 2023 Evaluating estuary water quality responses to reductions (or increases) in nutrient loading attributed to on the ground management actions can be challenging due to the strong influence of environmental drivers on nutrient loads and non-linear ...
Michael P. Schramm
doaj +3 more sources
Functional Generalized Additive Models. [PDF]
J Comput Graph Stat, 2014 We introduce the functional generalized additive model (FGAM), a novel regression model for association studies between a scalar response and a functional predictor. We model the link-transformed mean response as the integral with respect to t of F{X(t), t} where F(·,·) is an unknown regression function and X(t) is a functional covariate.
McLean MW +4 more
europepmc +4 more sources
Generalized Functional Additive Mixed Models
Electronic Journal of Statistics, 2016 We propose a comprehensive framework for additive regression models for non-Gaussian functional responses, allowing for multiple (partially) nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or
Gertheiss, Jan +2 more
core +4 more sources
Generalized Additive Models for Location Scale and Shape (GAMLSS) in R [PDF]
Journal of Statistical Software, 2007 GAMLSS is a general framework for fitting regression type models where the distribution of the response variable does not have to belong to the exponential family and includes highly skew and kurtotic continuous and discrete distribution.
D. Mikis Stasinopoulos, Robert A. Rigby
doaj +1 more source
The VGAM Package for Categorical Data Analysis [PDF]
Journal of Statistical Software, 2010 Classical categorical regression models such as the multinomial logit and proportional odds models are shown to be readily handled by the vector generalized linear and additive model (VGLM/VGAM) framework. Additionally, there are natural extensions, such
Thomas W. Yee
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
Generalized Additive Models [PDF]
Statistical Science, 1984 The classical linear regression model expresses the response vector Y as a function of the predictor variables \(X_ i\) through the model \(Y=\sum_{i}X_ i\beta_ i+e\), where the \(X_ i\) are observed, the \(\beta_ i\) are estimated by least squares or some other technique, e is the vector of errors.
Hastie, Trevor, Tibshirani, Robert
openaire +3 more sources