Results 141 to 150 of about 373,771 (313)

The Negative Binomial Distribution Efficiency in Finite Mixture of Semi-parametric Generalized Linear Models

پژوهش‌های ریاضی, 2019
Introduction Selection the appropriate statistical model for the response variable is one of the most important problem in the finite mixture of generalized linear models.
Farzad Eskandari
doaj  

Drought forecasting with regionalization of climate variables and generalized linear model

Meteorological Applications
Spring drought forecasting is essential in South Korea for managing water resources reliably and cultivating agricultural products efficiently, as seasonal rainfall difference often drives water shortage during spring.
Taesam Lee, Yejin Kong, Joo‐Heon Lee, Chang‐Hee Won   +3 more
doaj   +1 more source

Estimation of actual evapotranspiration in barley crop through a generalized linear model. [PDF]

MethodsX, 2022
Faramiñan A, Rodriguez PO, Carmona F, Holzman M, Rivas R, Mancino C.   +5 more
europepmc   +1 more source

Hierarchical Generalized Linear Models: The R Package HGLMMM

The R package HGLMMM has been developed to fit generalized linear models with random effects using the h-likelihood approach. The response variable is allowed to follow a binomial, Poisson, Gaussian or gamma distribution.
Marek Molas, Emmanuel Lesaffre
core  

Elevated Connectivity During Language Processing Is Associated With Cognitive Performance in SeLECTS

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Self‐Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross‐network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance.
Wendy Qi, Katharine Lee, Kerry C. Nix, Miguel Menchaca, Xiwei Shé, Lorelei Santa Maria, Wei Wu, Zihuai He, Fiona M. Baumer   +8 more
wiley   +1 more source

Next-Generation Sequencing Data-Based Association Testing of a Group of Genetic Markers for Complex Responses Using a Generalized Linear Model Framework. [PDF]

Mathematics (Basel), 2023
Xu Z, Yan S, Wu C, Duan Q, Chen S, Li Y.
europepmc   +1 more source

Generalized linear models

, 2015
AbstractGeneralized Linear Modeling (GLM) unifies several statistical techniques, providing a stable and modular foundation on which to build a useful working knowledge of statistical modeling. GLMs enable a re-interpretation of previously learned ANOVA and regression techniques and integrate well with more advanced modeling techniques introduced in ...
openaire   +5 more sources

Regularization Paths for Generalized Linear Models via Coordinate Descent

We develop fast algorithms for estimation of generalized linear models with convex penalties. The models include linear regression, two-class logistic regression, and multi- nomial regression problems while the penalties include âÂÂ_1 (the lasso), à ...
Trevor Hastie, Jerome H. Friedman, Rob Tibshirani   +2 more
core  

Designing experiments for binary data using search algorithms

, 2005
In some experiments in the physical and biological sciences, a binary response is of primary interest and is often described by a generalized linear model.
Lewis, S. M., Woods, D. C.
core  

Default Bayesian model determination methods for generalised linear mixed models

, 2010
In this paper, we consider a default strategy for fully Bayesian model determination for GLMMs. We address the two key issues of default prior specification and computation.
Overstall, Anthony M., Overstall, Antony, Forster, Jonathan, Overstall, Antony M., Forster, Jonathan J.   +4 more
core   +1 more source