Results 21 to 30 of about 1,274,599 (258)

Generalized linear mixed models can detect unimodal species-environment relationships [PDF]

open access: yesPeerJ, 2013
Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult to fit to data than linear ...
Tahira Jamil, Cajo J.F. ter Braak
doaj   +2 more sources

The OSCAR for Generalized Linear Models [PDF]

open access: yes, 2011
The Octagonal Selection and Clustering Algorithm in Regression (OSCAR) proposed by Bondell and Reich (2008) has the attractive feature that highly correlated predictors can obtain exactly the same coecient yielding clustering of predictors.
Petry, Sebastian, Tutz, Gerhard
core   +1 more source

Using R In Generalized Linear Models [PDF]

open access: yesRevista Română de Statistică, 2015
This paper aims to approach the estimation of generalized linear models (GLM) on the basis of the glm routine package in R. Particularly, regression models will be analyzed for those cases in which the explained variable follows a Poisson or a Negative ...
Mihaela Covrig   +4 more
doaj  

Tariff Analysis in Automobile Insurance: Is It Time to Switch from Generalized Linear Models to Generalized Additive Models?

open access: yesMathematics, 2023
Generalized Linear Models (GLMs) are the standard tool used for pricing in the field of automobile insurance. Generalized Additive Models (GAMs) are more complex and computationally intensive but allow taking into account nonlinear effects without the ...
Zuleyka Díaz Martínez   +2 more
doaj   +1 more source

Albatross analytics a hands-on into practice: statistical and data science application

open access: yesJournal of Big Data, 2022
Albatross Analytics is a statistical and data science data processing platform that researchers can use in disciplines of various fields. Albatross Analytics makes it easy to implement fundamental analysis for various regressions with random model ...
Rezzy Eko Caraka   +7 more
doaj   +1 more source

Holistic Generalized Linear Models

open access: yesJournal of Statistical Software
Holistic linear regression extends the classical best subset selection problem by adding additional constraints designed to improve the model quality.
Benjamin Schwendinger   +2 more
doaj   +1 more source

Comparison of predictor approaches for longitudinal binary outcomes: application to anesthesiology data [PDF]

open access: yesPeerJ, 2014
Longitudinal data with binary repeated responses are now widespread among clinical studies and standard statistical analysis methods have become inadequate in the answering of clinical hypotheses.
Anil Aktas Samur   +2 more
doaj   +2 more sources

Robust estimates in generalized partially linear models [PDF]

open access: yes, 2006
In this paper, we introduce a family of robust estimates for the parametric and nonparametric components under a generalized partially linear model, where the data are modeled by $y_i|(\mathbf{x}_i,t_i)\sim F(\cdot,\mu_i)$ with $\mu_i=H(\eta(t_i)+\mathbf{
Boente, Graciela   +2 more
core   +2 more sources

Multivariate Covariance Generalized Linear Models

open access: yes, 2015
We propose a general framework for non-normal multivariate data analysis called multivariate covariance generalized linear models (McGLMs), designed to handle multivariate response variables, along with a wide range of temporal and spatial correlation ...
Bonat, Wagner Hugo, Jørgensen, Bent
core   +1 more source

Generalized Linear Spatial Models to Predict Slate Exploitability

open access: yesJournal of Applied Mathematics, 2013
The aim of this research was to determine the variables that characterize slate exploitability and to model spatial distribution. A generalized linear spatial model (GLSMs) was fitted in order to explore relationship between exploitability and different ...
Angeles Saavedra   +3 more
doaj   +1 more source

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