Results 31 to 40 of about 1,274,632 (180)
Mathematics, 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
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The OSCAR for Generalized Linear Models [PDF]
, 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
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Using R In Generalized Linear Models [PDF]
Revista 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
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Albatross analytics a hands-on into practice: statistical and data science application
Journal 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
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Holistic Generalized Linear Models
Journal of Statistical SoftwareHolistic linear regression extends the classical best subset selection problem by adding additional constraints designed to improve the model quality.
Benjamin Schwendinger +2 more
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Comparison of predictor approaches for longitudinal binary outcomes: application to anesthesiology data [PDF]
PeerJ, 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
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Generalized Linear Spatial Models to Predict Slate Exploitability
Journal 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
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Multivariate Covariance Generalized Linear Models
, 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
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Efficient estimation of generalized linear latent variable models.
PLoS ONE, 2019 Generalized linear latent variable models (GLLVM) are popular tools for modeling multivariate, correlated responses. Such data are often encountered, for instance, in ecological studies, where presence-absences, counts, or biomass of interacting species ...
Jenni Niku +5 more
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Hyper-g Priors for Generalized Linear Models [PDF]
, 2010 We develop an extension of the classical Zellner's g-prior to generalized linear models. The prior on the hyperparameter g is handled in a flexible way, so that any continuous proper hyperprior f(g) can be used, giving rise to a large class of hyper-g ...
Bové, Daniel Sabanés, Held, Leonhard
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