Results 31 to 40 of about 467,081 (213)
Log-Linear Model and Multistate Model to Assess the Rate of Fibrosis in Patients With NAFLD
Frontiers in Applied Mathematics and Statistics, 2022 In this paper, the deleterious effects of obesity, type II diabetes, and insulin resistance, systolic and diastolic hypertension on the rate of progression of fibrosis in patients with non-alcoholic fatty liver disease (NAFLD) are illustrated using a new
Iman M. Attia
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IT SECTOR DEVELOPMENT IN CLUJ-NAPOCA. THE CASE OF SMEs
Studia Universitatis Babeş-Bolyai Negotia, 2015 The purpose of this paper is to to explore the evolution of SMEs from Cluj-Napoca in the IT sector by looking into the following problems: the relationship between number of employees, type of ownership and type of activity, as well as relationship ...
Ioan Cristian CHIFU +2 more
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Quasi‐Symmetric Graphical Log‐Linear Models [PDF]
Scandinavian Journal of Statistics, 2010 Abstract. We propose an extension of graphical log‐linear models to allow for symmetry constraints on some interaction parameters that represent homologous factors. The conditional independence structure of such quasi‐symmetric (QS) graphical models is described by an undirected graph with coloured edges, in which a particular colour corresponds to a ...
GOTTARD, ANNA +2 more
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Log-linear learning model for predicting a steady-state manual assembly time
Nonlinear Analysis, 2014 This paper presents the method for estimating the parameters of a two parameter learning curve (LC). Different values of parameters and different sample sizes are used for this estimation.
Vytautas Kleiza, Justinas Tilindis
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Annals of Emergency Medicine, 1993 Annals of Emergency Medicine 22 (1993) 1240-1240.
Division of Emergency Medicine University of Florida Health Science Center Jacksonville, USA ( host institution ) +1 more
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Beyond log-linear models [PDF]
Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies Short Papers - HLT '08, 2008 Current re-ranking algorithms for machine translation rely on log-linear models, which have the potential problem of underfitting the training data. We present BoostedMERT, a novel boosting algorithm that uses Minimum Error Rate Training (MERT) as a weak learner and builds a re-ranker far more expressive than log-linear models.
Kevin Duh, Katrin Kirchhoff
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BMC Bioinformatics, 2005 Background In testing for differential gene expression involving multiple serial analysis of gene expression (SAGE) libraries, it is critical to account for both between and within library variation.
Kepler Thomas B, Tomfohr John K, Lu Jun
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Graphical Local Genetic Algorithm for High-Dimensional Log-Linear Models
Mathematics, 2023 Graphical log-linear models are effective for representing complex structures that emerge from high-dimensional data. It is challenging to fit an appropriate model in the high-dimensional setting and many existing methods rely on a convenient class of ...
Lyndsay Roach, Xin Gao
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MathematicsThe Cox proportional hazards (PH) model is widely used because it models the covariates to the hazard through a log-linear effect. However, exploring flexible effects becomes desirable within the Cox PH framework when only a monotonic relationship ...
Huan Chen, Chuan-Fa Tang
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Exploring the association of anthropometric indicators for under-five children in Ethiopia
BMC Public Health, 2019 Background Child undernutrition is a global health concern. Many studies have focused on the association of childhood undernutrition indicators with their predictors. A few studies have looked at relationship between the undernutrition indicators.
Gashu Workneh Kassie +1 more
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