• Aucun résultat trouvé

[PDF] Top 20 Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature

Has 10000 "Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature" found on our website. Below are the top 20 most common "Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature".

Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature

Evaluation of the Fisher information matrix in nonlinear mixed effect models using adaptive Gaussian quadrature

... when the models are complex and have never been evaluated in design approaches, non- linearity measures (Bates and Watts, 1980; Cook and Goldberg, 1986) of the studied model should be ... Voir le document complet

29

A new method for evaluation of the Fisher information matrix for discrete mixed effect models using Monte Carlo sampling and adaptive Gaussian quadrature

A new method for evaluation of the Fisher information matrix for discrete mixed effect models using Monte Carlo sampling and adaptive Gaussian quadrature

... limitation of the approach presentedis a consequence of the curse of dimensional- ...ity. The number of model evaluations increases exponentially with the number ... Voir le document complet

26

Influence of covariance between random effects in design for nonlinear mixed-effect models with an illustration in pediatric pharmacokinetics.

Influence of covariance between random effects in design for nonlinear mixed-effect models with an illustration in pediatric pharmacokinetics.

... extend the Fisher information matrix in PFIM software for covariance between random effects and to evaluate ...For the evaluation, a comparison of the SEs ... Voir le document complet

37

Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0

Design evaluation and optimisation in multiple response nonlinear mixed effect models: PFIM 3.0

... number of parameters to optimise, or when the model is complex, it could have difficulties in converging towards the optimal design and should sometimes be run again using the ... Voir le document complet

37

saemix, an R version of the SAEM algorithm for parameter estimation in nonlinear mixed effect models

saemix, an R version of the SAEM algorithm for parameter estimation in nonlinear mixed effect models

... Results: The library uses the S4 lass system of R to provide a user-friendly input and output system, with methods like summary or plot for tted obje ...ts. The pa kage provides summaries ... Voir le document complet

3

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

... studied in crossover design and can be analysed by nonlinear mixed effects models as an alternative to noncompartmental ...extension of the population Fisher ... Voir le document complet

27

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

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

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 ...instance in nlme and lme4. The different packages all have their own ... Voir le document complet

43

Fisher Information Matrix for Optimizing the Acquisition Parameters in Multi-Parametric Mapping Based on Fast Steady-State Sequences

Fisher Information Matrix for Optimizing the Acquisition Parameters in Multi-Parametric Mapping Based on Fast Steady-State Sequences

... as in protocol 4, more precise estimates with mo re uniform errors are obtained in a wider ...Optimization of acquisition parameters through the CRLB may provide a valuable tool for objective ... Voir le document complet

8

Bivariate linear mixed models using SAS proc MIXED.

Bivariate linear mixed models using SAS proc MIXED.

... as the infection measured by HIV RNA induces inflammation and the destruction of immune ...evolution of CD4 and CD8 cells [4] or CD4 and  2 microglobuline ...used the Fisher ... Voir le document complet

20

Adaptive Laguerre density estimation for mixed Poisson models

Adaptive Laguerre density estimation for mixed Poisson models

... nonparametric adaptive strategy to estimate f ...build adaptive projection estimators. Non-asymptotic upper bounds of the L 2 -integrated risk are obtained and a lower bound is provided, which ... Voir le document complet

29

Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: The npde add-on package for R.

Computing normalised prediction distribution errors to evaluate nonlinear mixed-effect models: The npde add-on package for R.

... for the estimation, these data should be removed from the dataset or set to missing, using for example an MDV item, pending future extensions of npde ...On the other hand, if BQL data ... Voir le document complet

41

Time-local discretization of fractional and related diffusive operators using Gaussian quadrature with applications

Time-local discretization of fractional and related diffusive operators using Gaussian quadrature with applications

... objective of this paper is to investigate the discretization of diffusive representations using Gaussian quadrature, for application in the numerical solution ... Voir le document complet

21

Nonlinear spectral unmixing of hyperspectral images using Gaussian processes

Nonlinear spectral unmixing of hyperspectral images using Gaussian processes

... distribution in the following set (36) The three resulting images are denoted as , and ...that the absence of pure pixels does not change the AREs signiÞcantly when they are ... Voir le document complet

13

New adaptive strategies for nonparametric estimation in linear mixed models

New adaptive strategies for nonparametric estimation in linear mixed models

... for the estimation of ...all the available ...performed. The particularity here is the selection model procedure: we adapt a method set up in Goldenshluger and Lepski (2011) for ... Voir le document complet

23

Nonlinear MIMO communication systems : channel estimation and information recovery using Volterra models

Nonlinear MIMO communication systems : channel estimation and information recovery using Volterra models

... Some of the channel estimation techniques proposed in this thesis make use of a training sequence known by both transmitter and receiver during the acquisition ...period. In this ... Voir le document complet

241

Fisher information and the Fourth Moment Theorem

Fisher information and the Fourth Moment Theorem

... Keywords: Fisher information; total variation distance; relative entropy; Fourth Moment Theorem; Fractional Brownian motion; Malliavin ...Measuring the discrepancy between the law of a ... Voir le document complet

24

Evaluation of expert-based Q-Matrices predictive quality in matrix factorization models

Evaluation of expert-based Q-Matrices predictive quality in matrix factorization models

... Abstract. Matrix factorization techniques are widely used to build col- laborative filtering recommender ...predict the interest of users. In cognitive modeling, skills and competencies are ... Voir le document complet

15

Control-Based Continuation of Nonlinear Structures Using Adaptive Filtering

Control-Based Continuation of Nonlinear Structures Using Adaptive Filtering

... Control, Nonlinear Vibrations, Experimen- tal Characterization State of the art of Control-Based Continuation The characterization of a nonlinear structure consists ... Voir le document complet

4

Show all 10000 documents...