Non-linear mixed effects models
A comparison of bootstrap approaches for estimating uncertainty of parameters in linear mixed-effects models.
... random effects and residuals were resampled remained the best methods and selected as bootstrap candidates for linear mixed-effects ...with linear mixed-effects ...the ...
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Estimating Markov and semi-Markov switching linear mixed models with individual-wise random effects
... switching linear mixed models i.e. models that combine linear mixed models with individual- wise random effects in a (semi-)Markovian ...random effects, ...
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Standard errors of solutions in large scale mixed models, application to linear and curvilinear effects of inbreeding on production traits.
... Key Words: Diseases and Production, Structural Equation Model, Simultane- ity 27 Standard errors of solutions in large scale mixed models, applica- tion to linear and curvilinear effects of ...
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Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.
... levels non-linear mixed effects ...random effects are the between-subject variance and the within-subject (or between-unit) variance, with N subjects and K units, with no restriction on ...
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The SAEM algorithm for group comparison tests in longitudinal data analysis based on non-linear mixed-effects model.
... data; Non-linear mixed effects models; SAEM algorithm; sample ...on linear or non-linear mixed-effects models ...Such models have been ...
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Estimation of linear mixed models with a mixture of distribution for the random-effects
... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ...
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Markov and semi-Markov switching linear mixed models for identifying forest tree growth components.
... random effects or by the linear mixed model (2) in the case of individual-state-wise random ...random effects are incorporated in the output process, the successive observations for an ...
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Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models
... The work presented here focusses on crossover PK trials analysed by NLMEM. Before the modelling step, data needs to be collected and we have consequently to define an appropriate de- sign , which consists of determining ...
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Bivariate linear mixed models using SAS proc MIXED.
... Bivariate linear mixed models are useful when analyzing longitudinal data of two associated ...bivariate linear mixed model including random effects or first-order ...
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Extension to mixed models of the Supervised Component-based Generalised Linear Regression
... Besides, regularisation methods have already been developped for GLMM, in which the random effects allow to model complex dependence structure. Eliot et al. [ 3 ] proposed to extend the classical ridge regression ...
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Modelling finger force produced from different tasks using linear mixed models with lme R function
... The biomechanical data considered in this paper are obtained from a study carried out to understand the coordination patterns of finger forces produced from different tasks. This data cannot be considered independent ...
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New adaptive strategies for nonparametric estimation in linear mixed models
... in linear mixed-effects ...them, non-asymptotic L 2 -risk bounds are established implying estimation rates, much better than the expected deconvolution ...
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Linear and non-linear price decentralization
... economic models and the large literature on price decentralization in vector lattices has little, that is obvious, to say in such a ...such models all the decentralization results can fail even if the ...
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Effects of non-linear GJ channels on the AP propagation : a modelling insight
... Effects of non-linear GJ channels on the AP propagation : a modelling insight Yves Coudière 1, 2, 3, 4 , Anđela Davidović 1, 2, 3, 4 , Thomas Desplantez 2, 4, 5 , Clair Poignard 1, 2, 3 1 INRIA ...
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Toward robust parameterized reduced-order models of non-linear structures using POD
... S. Hoffait, G. Kerschen, O. Brüls LTAS - Department of Aerospace and Mechanical Engineering, Université de Liège, Belgium, {sebastien.hoffait,g.kerschen,o.bruls}@ulg.ac.be This work addresses the development of robust ...
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Models for mixed – species forests
... In all, this modelling approach is useful to detect, quantify, and hierarchize effects of site index, stand density and mixture effects, provided that height and diameter are measured (very few required ...
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Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.
... Comparison of the estimated Gaussian hidden semi-Markov chain (GHSMC) parameters (i.e. where the influence of covariates and the inter-individual heterogeneity are not taken into account) with the estimated semi-Markov ...
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Convex optimization in identification of stable non-linear state space models
... t |˜ x(t + 1) − f (˜ x(t), ˜ u(t))| 2 , or similar, over the unknown parameters of f(·). A similar optimization can be set up for g(·). This is typically very cheap computationally, often reducing to basic least squares. ...
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Recursive linearly constrained minimum variance estimator in linear models with non-stationary constraints
... a linear regression ...or non-stationary environments, giving rise to well-established recursive adaptive implementations when multiple observations are ...of non-stationary constraints leading to ...
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Low loss microstructured chalcogenide fibers for large non linear effects at 1995 nm.
... large non linear optical ...optical non linearity. The non linear refractive index of sulfur based glasses is over 100 times larger than silica ...The non linear index of ...
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