Results 1 to 10 of about 280,435 (260)

Federated generalized additive models for location, scale and shape [PDF]

open access: yesBMC Medical Research Methodology
Background 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]

open access: yesPeerJ, 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]

open access: yesPeerJ, 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]

open access: yesJ 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

open access: yesElectronic 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

Detecting contaminated birthdates using generalized additive models. [PDF]

open access: yesBMC Bioinformatics, 2014
Erroneous patient birthdates are common in health databases. Detection of these errors usually involves manual verification, which can be resource intensive and impractical. By identifying a frequent manifestation of birthdate errors, this paper presents
Luo W   +5 more
europepmc   +3 more sources

Generalized Additive Models for Location Scale and Shape (GAMLSS) in R [PDF]

open access: yesJournal 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]

open access: yesJournal 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

Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape [PDF]

open access: yesFrontiers in Psychology, 2018
As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because ...
Christophe Coupé
doaj   +2 more sources

Meta-analysis of generalized additive models in neuroimaging studies

open access: yesNeuroImage, 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

Home - About - Disclaimer - Privacy