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[PDF] Top 20 Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.

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Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.

Extension of the SAEM algorithm for nonlinear mixed models with 2 levels of random effects.

... Discussion The main original element of this study is the development of the SAEM algorithm for two- levels non-linear mixed effects ...extend ... Voir le document complet

30

Modelisation and estimation of heterogeneous variances in nonlinear mixed models

Modelisation and estimation of heterogeneous variances in nonlinear mixed models

... Introduction Nonlinear mixed effects models (NLMM) are more and more frequently used for anal- ysis of longitudinal data and repeated measurements in pharmacokinetics, growth and ... Voir le document complet

187

Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

Evaluation of bootstrap methods for estimating uncertainty of parameters in nonlinear mixed-effects models: a simulation study in population pharmacokinetics

... evaluating the inverse of the M F . The bootstrap is an alternative method to assess the uncertainty of parameters without making strong distributional ...(1979) for ... Voir le document complet

29

Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm

Parameter Estimation in Nonlinear Mixed Effect Models Using saemix, an R Implementation of the SAEM Algorithm

... implementation of one of these recent estimation algorithms, SAEM, in R, to obtain maximum likelihood ...implemented for instance in nlme and lme4. The different packages all have their ... Voir le document complet

43

Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model.

Fisher information matrix for nonlinear mixed effects multiple response models: evaluation of the appropriateness of the first order linearization using a pharmacokinetic/pharmacodynamic model.

... distribution of the observed RSE when M F is computed by the Louis’s principle [30] compared to the RSE observed with the linearization ...Although the approach using ... Voir le document complet

30

Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.: Alternatives to Asymptotic Tests in NLMEM: an Application to Pharmacogenetics

Some alternatives to asymptotic tests for the analysis of pharmacogenetic data using nonlinear mixed effects models.: Alternatives to Asymptotic Tests in NLMEM: an Application to Pharmacogenetics

... Summary: Nonlinear mixed effects models allow investigating individual differences in drug con- centration profiles (pharmacokinetics) and ...on the genetic component of this ... Voir le document complet

28

Extension of NPDE for evaluation of nonlinear mixed effect models in presence of data below the quantification limit with applications to HIV dynamic model.

Extension of NPDE for evaluation of nonlinear mixed effect models in presence of data below the quantification limit with applications to HIV dynamic model.

... spite of some problems of the Fisher tests, type I errors for the npde computed by the new method, especially those of the global test, are very close to 5% and ... Voir le document complet

32

Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model

Extension of the SAEM algorithm to left-censored data in nonlinear mixed-effects model: Application to HIV dynamics model

... describing the model and the notations (Section 2), Section 3 de- scribes the extended SAEM ...reports the simulation study and its results. We simulate datasets using the ... Voir le document complet

25

Performance in population models for count data, part II: a new SAEM algorithm.

Performance in population models for count data, part II: a new SAEM algorithm.

... Overall, the estimation procedure with the SAEM algorithm in a non-linear mixed effect modelling framework for count data models, showed satisfactory performance ... Voir le document complet

32

Sensitivity analysis with dependent random variables : Estimation of the Shapley effects for unknown input distribution and linear Gaussian models

Sensitivity analysis with dependent random variables : Estimation of the Shapley effects for unknown input distribution and linear Gaussian models

... • Random Forest, from the R package randomForest, which optimizes auto- matically the parameters by ...estimate the value of Var(E(Y |X))/Var(Y ) to ...denotes the output ... Voir le document complet

299

A comparison of bootstrap approaches for estimating uncertainty of parameters in linear mixed-effects models.

A comparison of bootstrap approaches for estimating uncertainty of parameters in linear mixed-effects models.

... estimates of variance components in many situations [2, 3] . The standard errors (SE) of parameter estimates are obtained asymptotically from the in- verse of the Fisher ... Voir le document complet

37

On the Wave Turbulence Theory for the Nonlinear Schrödinger Equation with Random Potentials

On the Wave Turbulence Theory for the Nonlinear Schrödinger Equation with Random Potentials

... on the original equation were done in [ 5 , 6 , 10 ], in which they get the 1/3 growth, pointing to the six-wave equation discussed in our ...Moreover, with extra dephasing, the growth ... Voir le document complet

13

Mixed-radix Algorithm for the Computation of Forward and Inverse MDCT.

Mixed-radix Algorithm for the Computation of Forward and Inverse MDCT.

... two of the most computational intensive operations in MPEG audio coding ...new mixed-radix algorithm for efficient computing the MDCT/IMDCT is ...presented. The proposed ... Voir le document complet

13

Virtual Extension of Meta-models with Facet Tools

Virtual Extension of Meta-models with Facet Tools

... (NI-MM for short), a composition that preserves the compo- nents, is called the "model-based correspondence" by Clavreul who identified 88 techniques for different purposes in his ... Voir le document complet

9

Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models

Design evaluation and optimisation in crossover pharmacokinetic studies analysed by nonlinear mixed effects models

... handling the left-censored data in NLMEM as an exact Maximum Likelihood estimation ...calculate the empirical SE, defined as the sample estimate of the standard deviation from ... Voir le document complet

27

Pharmacogenetics and population pharmacokinetics: impact of the design on three tests using the SAEM algorithm.

Pharmacogenetics and population pharmacokinetics: impact of the design on three tests using the SAEM algorithm.

... For the Wald test, we relate this inflation to the under-estimation of the SE of the gene effect ...performed the Wald test using the empirical SE rather ... Voir le document complet

16

Extension of Partitional Clustering Methods for Handling Mixed Data

Extension of Partitional Clustering Methods for Handling Mixed Data

... in the literature. Most of these methods are based on the use of a distance measure defined either on numerical attributes or on categorical at- ...composed of numerical and categorical ... Voir le document complet

10

BIC selection procedures in mixed effects models

BIC selection procedures in mixed effects models

... 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] ... Voir le document complet

21

Extension of Random Matrix Theory to the L-moments for Robust Portfolio Allocation

Extension of Random Matrix Theory to the L-moments for Robust Portfolio Allocation

... question the one factor model and show that except the market factor, others risk factors exist and should be took into account (see Black, Jensen and Scholes, 1972), this is at the origin of ... Voir le document complet

42

Fixed versus Random Effects in Poisson Regression Models for Claim Counts

Fixed versus Random Effects in Poisson Regression Models for Claim Counts

... only the estimate of β F E is consistent for fixed T and N → ∞, as for insurance ...Application of the fixed effects Poisson model to the Belgian motor portfolio ... Voir le document complet

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