Haut PDF 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
... Finally, the robustness of the estimated parameters can be assessed by changing the random seed (argument seed) and initial estimates of the parameters around the final ...
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saemix, an R version of the SAEM algorithm for parameter estimation in nonlinear mixed effect models
... tion: The use of modelling and simulation in lini
al drug development is now well ...Regardless of whether a single out
ome is onsidered at the end of the study, lini
al ...
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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 ...
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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 ...
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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 ...
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Implementation and Evaluation of the SAEM algorithm for longitudinal ordered categorical data with an illustration in pharmacokinetics-pharmacodynamics
... likelihood estimation. However, as in all nonlinear mixed models, the integral of the likelihood function cannot be explicitly solved and various approximations are ...
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Nonlinear MIMO communication systems : channel estimation and information recovery using Volterra models
... Volterra Models for Nonlinear MIMO Communica- tion Systems, provides an overview of MIMO Volterra models in the context of nonlinear communication systems, ...
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New adaptive strategies for nonparametric estimation in linear mixed models
... for the estimation of ...propose an estimator which uses all the available ...performed. The particularity here is the selection model procedure: we adapt a method set up ...
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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 much more ...
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State and parameter estimation for a class of schistosomiasis models
... implemented in an attempt to eradicate schistosomiasis or alleviate its morbidity in many endemic countries [ 34 ...degrees of success. However, this method has its own set of ...
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An Implementation of the Shooting Algorithm for Solving Optimal Control Problems
... Unit´e de recherche INRIA Lorraine, Technopˆole de Nancy-Brabois, Campus scientifique, ` NANCY 615 rue du Jardin Botanique, BP 101, 54600 VILLERS LES Unit´e de recherche INRIA Rennes, Ir[r] ...
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Latent parameter estimation in fusion networks using separable likelihoods
... [26] in which windowing of measurements are used for enabling online ...results of the proposed pseudo-likelihood can be found in ...account of our solution strategy in ...
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Bivariate linear mixed models using SAS proc MIXED.
... The APROCO (ANRS-EP11) cohort is a prospective observational cohort ongoing in 47 clinical centres in ...total of 1,281 HIV-1-infected patients were enrolled from May 1997 to June 1999 at ...
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FrailtyPack: An R Package for the Analysis of Correlated Survival Data with Frailty Models Using Penalized Likelihood or Parametrical Estimation
... groups. The nested frailty model 6 is most appropriate, when there are two levels of hierarchical ...increase the risk of death, thus the terminal event is considered as an ...
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clogitLasso: an R package for L1 penalized estimation of conditional logistic regression models
... epidemiology. The conditional logistic regression model is the standard tool for the analysis of epidemiological studies in which one or more cases (the event of ...
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Cardiovascular parameter estimation using a computational model
... The plot also shows the reconstruction of the same data portion using exact parameter values and estimated initial conditions which neglect the volume of fluid administe[r] ...
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Comparison of cardiovascular parameter estimation methods using swine data
... The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Citation Arai, Tatsuya et al., "Comparison of cardiovascular parameter ...
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Modelling finger force produced from different tasks using linear mixed models with lme R function
... Conclusion In this paper, we have proposed a methodology to handle with biomechanical ...data. The main features of these data lie in the repetition of the force inten- ...
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Nonlinear regression using smooth Bayesian estimation
... considered in this paper (see [8] for more details about these methods). The main contribution of this paper is the elaboration of a hierarchical Bayesian model that allows smooth ...
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Parametric estimation of complex mixed models based on meta-model approach
... of simplicity, the estimation of σ ε may be less accurate but usually this parameter if of less ...remarks In the case of a mixed model where ...
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