Log in

Relevant bibliographies by topics / Nonlinear mixed-effects model

Contents

Journal articles
Dissertations / Theses
Books
Book chapters
Conference papers

Academic literature on the topic 'Nonlinear mixed-effects model'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Nonlinear mixed-effects model.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Journal articles on the topic "Nonlinear mixed-effects model"

1

Craig, B. A., and A. P. Schinckel. "Nonlinear Mixed Effects Model for Swine Growth." Professional Animal Scientist 17, no. 4 (December 2001): 256–60. http://dx.doi.org/10.15232/s1080-7446(15)31637-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Harring, Jeffrey R. "A Nonlinear Mixed Effects Model for Latent Variables." Journal of Educational and Behavioral Statistics 34, no. 3 (September 2009): 293–318. http://dx.doi.org/10.3102/1076998609332750.

Full text

Abstract:

The nonlinear mixed effects model for continuous repeated measures data has become an increasingly popular and versatile tool for investigating nonlinear longitudinal change in observed variables. In practice, for each individual subject, multiple measurements are obtained on a single response variable over time or condition. This structure can be adapted to examine the change in latent variables rather than modeling change in manifest variables. This article considers a nonlinear mixed effects model for describing nonlinear change of a latent construct over time, where the latent construct of interest is measured by multiple indicators gathered at each measurement occasion. To accomplish this, the nonlinear mixed effects model is modified to include a measurement model that explicitly expresses the relationship of the observed variables to the latent constructs. A method for marginal maximum likelihood estimation of this model is presented and discussed. An example using education data is provided to illustrate the utility of the model.

APA, Harvard, Vancouver, ISO, and other styles

3

Funatogawa, Ikuko, and Takashi Funatogawa. "Fundamentals in Population Pharmacokinetics: Mathematics in Linear Mixed Effects Model and Nonlinear Mixed Effects Model." Japanese Journal of Biometrics 36, Special_Issue (2015): S33—S48. http://dx.doi.org/10.5691/jjb.36.s33.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Li, Yao Xiang, and Li Chun Jiang. "Fitting Growth Model Using Nonlinear Regression with Random Parameters." Key Engineering Materials 480-481 (June 2011): 1308–12. http://dx.doi.org/10.4028/www.scientific.net/kem.480-481.1308.

Full text

Abstract:

Mixed Effect models are flexible models to analyze grouped data including longitudinal data, repeated measures data, and multivariate multilevel data. One of the most common applications is nonlinear growth data. The Chapman-Richards model was fitted using nonlinear mixed-effects modeling approach. Nonlinear mixed-effects models involve both fixed effects and random effects. The process of model building for nonlinear mixed-effects models is to determine which parameters should be random effects and which should be purely fixed effects, as well as procedures for determining random effects variance-covariance matrices (e.g. diagonal matrices) to reduce the number of the parameters in the model. Information criterion statistics (AIC, BIC and Likelihood ratio test) are used for comparing different structures of the random effects components. These methods are illustrated using the nonlinear mixed-effects methods in S-Plus software.

APA, Harvard, Vancouver, ISO, and other styles

5

Aggrey, S. E. "Logistic nonlinear mixed effects model for estimating growth parameters." Poultry Science 88, no. 2 (February 2009): 276–80. http://dx.doi.org/10.3382/ps.2008-00317.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Elmi, Angelo, Sarah J. Ratcliffe, Samuel Parry, and Wensheng Guo. "A B-Spline Based Semiparametric Nonlinear Mixed Effects Model." Journal of Computational and Graphical Statistics 20, no. 2 (January 2011): 492–509. http://dx.doi.org/10.1198/jcgs.2010.09001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Davidian, Marie, and David M. Giltinan. "Some general estimation methods for nonlinear mixed-effects model." Journal of Biopharmaceutical Statistics 3, no. 1 (January 1, 1993): 23–55. http://dx.doi.org/10.1080/10543409308835047.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

DAVIDIAN, MARIE, and A. RONALD GALLANT. "The nonlinear mixed effects model with a smooth random effects density." Biometrika 80, no. 3 (1993): 475–88. http://dx.doi.org/10.1093/biomet/80.3.475.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Williams, Donald R., Daniel R. Zimprich, and Philippe Rast. "A Bayesian nonlinear mixed-effects location scale model for learning." Behavior Research Methods 51, no. 5 (May 8, 2019): 1968–86. http://dx.doi.org/10.3758/s13428-019-01255-9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Frutos, G., and M. C. Ruiz de Villa. "Nonlinear mixed-effects model for the dissolution assays of drugs." Journal of Controlled Release 94, no. 2-3 (February 2004): 381–89. http://dx.doi.org/10.1016/j.jconrel.2003.10.017.

Full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Dissertations / Theses on the topic "Nonlinear mixed-effects model"

1

Ribbing, Jakob. "Covariate Model Building in Nonlinear Mixed Effects Models." Doctoral thesis, Uppsala : Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7923.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Gibiansky, Ekaterina. "Population pharmacokinetics : model-free approach and nonlinear mixed-effects modelling." Thesis, University of Greenwich, 1999. http://gala.gre.ac.uk/8654/.

Full text

Abstract:

The work is devoted to the application and further development of modern statistical methods to study pharmacokinetics of drugs. Specifically, it deals with applications and development of repeated measures analysis, so called 'population approach' methods, in the field of pharmacokinetics. hi the first part of the thesis, a new, model-free approach is developed and tested. It introduces a model-free measure of patient's exposure to drugs, and then investigates the relationships between the exposure level and covariates using various statistical techniques. Classification tree models (CART) and regression analysis are used to study various subpopulations of interest. It is shown, via simulations, that the model-free method is capable to identify predictors of exposure in a wide range of variability in the data. The non-linear mixed effect modelling is used to confirm the results of the model-free investigation. Model-free approach is successfully applied to several drugs. Non-linear Mixed Effects population models developed for the same data agree with its results. Limits of the new method are also identified. Specifically, it does not allow the estimation of the variability: either the within-subject (intra-individual) variability in response, or between-subject (inter-individual) variability of the pharmacokinetic parameters in the population. The second part of the thesis is devoted to applications of the Non-linear Mixed Effect methodology to population pharmacokinetics and dose-response analysis. Population pharmacokinetic and dose-response models of several drugs are developed. Pharmacokinetic models allow for complete characterisation of the drug's pharmacokinetics and its relationships to safety and efficacy. The developed models are used to explore the relationships between the exposure (individual Bayes estimates) and demographic predictors of exposure, and safety and efficacy of the drug. Finally, the developed models are used in simulations to guide the design of new studies.

APA, Harvard, Vancouver, ISO, and other styles

3

Cole, James Jacob. "Assessing Nonlinear Relationships through Rich Stimulus Sampling in Repeated-Measures Designs." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/dissertations/1587.

Full text

Abstract:

Explaining a phenomenon often requires identification of an underlying relationship between two variables. However, it is common practice in psychological research to sample only a few values of an independent variable. Young, Cole, and Sutherland (2012) showed that this practice can impair model selection in between-subject designs. The current study expands that line of research to within-subjects designs. In two Monte Carlo simulations, model discrimination under systematic sampling of 2, 3, or 4 levels of the IV was compared with that under random uniform sampling and sampling from a Halton sequence. The number of subjects, number of observations per subject, effect size, and between-subject parameter variance in the simulated experiments were also manipulated. Random sampling out-performed the other methods in model discrimination with only small, function-specific costs to parameter estimation. Halton sampling also produced good results but was less consistent. The systematic sampling methods were generally rank-ordered by the number of levels they sampled.

APA, Harvard, Vancouver, ISO, and other styles

4

Zhang, Huaiye. "Bayesian Approach Dealing with Mixture Model Problems." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/37681.

Full text

Abstract:

In this dissertation, we focus on two research topics related to mixture models. The first topic is Adaptive Rejection Metropolis Simulated Annealing for Detecting Global Maximum Regions, and the second topic is Bayesian Model Selection for Nonlinear Mixed Effects Model. In the first topic, we consider a finite mixture model, which is used to fit the data from heterogeneous populations for many applications. An Expectation Maximization (EM) algorithm and Markov Chain Monte Carlo (MCMC) are two popular methods to estimate parameters in a finite mixture model. However, both of the methods may converge to local maximum regions rather than the global maximum when multiple local maxima exist. In this dissertation, we propose a new approach, Adaptive Rejection Metropolis Simulated Annealing (ARMS annealing), to improve the EM algorithm and MCMC methods. Combining simulated annealing (SA) and adaptive rejection metropolis sampling (ARMS), ARMS annealing generate a set of proper starting points which help to reach all possible modes. ARMS uses a piecewise linear envelope function for a proposal distribution. Under the SA framework, we start with a set of proposal distributions, which are constructed by ARMS, and this method finds a set of proper starting points, which help to detect separate modes. We refer to this approach as ARMS annealing. By combining together ARMS annealing with the EM algorithm and with the Bayesian approach, respectively, we have proposed two approaches: an EM ARMS annealing algorithm and a Bayesian ARMS annealing approach. EM ARMS annealing implement the EM algorithm by using a set of starting points proposed by ARMS annealing. ARMS annealing also helps MCMC approaches determine starting points. Both approaches capture the global maximum region and estimate the parameters accurately. An illustrative example uses a survey data on the number of charitable donations. The second topic is related to the nonlinear mixed effects model (NLME). Typically a parametric NLME model requires strong assumptions which make the model less flexible and often are not satisfied in real applications. To allow the NLME model to have more flexible assumptions, we present three semiparametric Bayesian NLME models, constructed with Dirichlet process (DP) priors. Dirichlet process models often refer to an infinite mixture model. We propose a unified approach, the penalized posterior Bayes factor, for the purpose of model comparison. Using simulation studies, we compare the performance of two of the three semiparametric hierarchical Bayesian approaches with that of the parametric Bayesian approach. Simulation results suggest that our penalized posterior Bayes factor is a robust method for comparing hierarchical parametric and semiparametric models. An application to gastric emptying studies is used to demonstrate the advantage of our estimation and evaluation approaches.
Ph. D.

APA, Harvard, Vancouver, ISO, and other styles

5

Dosne, Anne-Gaëlle. "Improved Methods for Pharmacometric Model-Based Decision-Making in Clinical Drug Development." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-305697.

Full text

Abstract:

Pharmacometric model-based analysis using nonlinear mixed-effects models (NLMEM) has to date mainly been applied to learning activities in drug development. However, such analyses can also serve as the primary analysis in confirmatory studies, which is expected to bring higher power than traditional analysis methods, among other advantages. Because of the high expertise in designing and interpreting confirmatory studies with other types of analyses and because of a number of unresolved uncertainties regarding the magnitude of potential gains and risks, pharmacometric analyses are traditionally not used as primary analysis in confirmatory trials. The aim of this thesis was to address current hurdles hampering the use of pharmacometric model-based analysis in confirmatory settings by developing strategies to increase model compliance to distributional assumptions regarding the residual error, to improve the quantification of parameter uncertainty and to enable model prespecification. A dynamic transform-both-sides approach capable of handling skewed and/or heteroscedastic residuals and a t-distribution approach allowing for symmetric heavy tails were developed and proved relevant tools to increase model compliance to distributional assumptions regarding the residual error. A diagnostic capable of assessing the appropriateness of parameter uncertainty distributions was developed, showing that currently used uncertainty methods such as bootstrap have limitations for NLMEM. A method based on sampling importance resampling (SIR) was thus proposed, which could provide parameter uncertainty in many situations where other methods fail such as with small datasets, highly nonlinear models or meta-analysis. SIR was successfully applied to predict the uncertainty in human plasma concentrations for the antibiotic colistin and its prodrug colistin methanesulfonate based on an interspecies whole-body physiologically based pharmacokinetic model. Lastly, strategies based on model-averaging were proposed to enable full model prespecification and proved to be valid alternatives to standard methodologies for studies assessing the QT prolongation potential of a drug and for phase III trials in rheumatoid arthritis. In conclusion, improved methods for handling residual error, parameter uncertainty and model uncertainty in NLMEM were successfully developed. As confirmatory trials are among the most demanding in terms of patient-participation, cost and time in drug development, allowing (some of) these trials to be analyzed with pharmacometric model-based methods will help improve the safety and efficiency of drug development.

APA, Harvard, Vancouver, ISO, and other styles

6

Strömberg, Eric. "Applied Adaptive Optimal Design and Novel Optimization Algorithms for Practical Use." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-308452.

Full text

Abstract:

The costs of developing new pharmaceuticals have increased dramatically during the past decades. Contributing to these increased expenses are the increasingly extensive and more complex clinical trials required to generate sufficient evidence regarding the safety and efficacy of the drugs. It is therefore of great importance to improve the effectiveness of the clinical phases by increasing the information gained throughout the process so the correct decision may be made as early as possible. Optimal Design (OD) methodology using the Fisher Information Matrix (FIM) based on Nonlinear Mixed Effect Models (NLMEM) has been proven to serve as a useful tool for making more informed decisions throughout the clinical investigation. The calculation of the FIM for NLMEM does however lack an analytic solution and is commonly approximated by linearization of the NLMEM. Furthermore, two structural assumptions of the FIM is available; a full FIM and a block-diagonal FIM which assumes that the fixed effects are independent of the random effects in the NLMEM. Once the FIM has been derived, it can be transformed into a scalar optimality criterion for comparing designs. The optimality criterion may be considered local, if the criterion is based on singe point values of the parameters or global (robust), where the criterion is formed for a prior distribution of the parameters. Regardless of design criterion, FIM approximation or structural assumption, the design will be based on the prior information regarding the model and parameters, and is thus sensitive to misspecification in the design stage. Model based adaptive optimal design (MBAOD) has however been shown to be less sensitive to misspecification in the design stage. The aim of this thesis is to further the understanding and practicality when performing standard and MBAOD. This is to be achieved by: (i) investigating how two common FIM approximations and the structural assumptions may affect the optimized design, (ii) reducing runtimes complex design optimization by implementing a low level parallelization of the FIM calculation, (iii) further develop and demonstrate a framework for performing MBAOD, (vi) and investigate the potential advantages of using a global optimality criterion in the already robust MBAOD.

APA, Harvard, Vancouver, ISO, and other styles

7

Clewe, Oskar. "Novel Pharmacometric Methods for Informed Tuberculosis Drug Development." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-303872.

Full text

Abstract:

With approximately nine million new cases and the attributable cause of death of an estimated two millions people every year there is an urgent need for new and effective drugs and treatment regimens targeting tuberculosis. The tuberculosis drug development pathway is however not ideal, containing non-predictive model systems and unanswered questions that may increase the risk of failure during late-phase drug development. The aim of this thesis was hence to develop pharmacometric tools in order to optimize the development of new anti-tuberculosis drugs and treatment regimens. The General Pulmonary Distribution model was developed allowing for prediction of both rate and extent of distribution from plasma to pulmonary tissue. A distribution characterization that is of high importance as most current used anti-tuberculosis drugs were introduced into clinical use without considering the pharmacokinetic properties influencing drug distribution to the site of action. The developed optimized bronchoalveolar lavage sampling design provides a simplistic but informative approach to gathering of the data needed to allow for a model based characterization of both rate and extent of pulmonary distribution using as little as one sample per subject. The developed Multistate Tuberculosis Pharmacometric model provides predictions over time for a fast-, slow- and non-multiplying bacterial state with and without drug effect. The Multistate Tuberculosis Pharmacometric model was further used to quantify the in vitro growth of different strains of Mycobacterium tuberculosis and the exposure-response relationships of three first line anti-tuberculosis drugs. The General Pharmacodynamic Interaction model was successfully used to characterize the pharmacodynamic interactions of three first line anti-tuberculosis drugs, showing the possibility of distinguishing drug A’s interaction with drug B from drug B’s interaction with drug A. The successful separation of all three drugs effect on each other is a necessity for future work focusing on optimizing the selection of anti-tuberculosis combination regimens. With a focus on pharmacokinetics and pharmacodynamics, the work included in this thesis provides multiple new methods and approaches that individually, but maybe more important the combination of, has the potential to inform development of new but also to provide additional information of the existing anti-tuberculosis drugs and drug regimen.

APA, Harvard, Vancouver, ISO, and other styles

8

Nagem, Mohamed O. "Diagnostics for Nonlinear Mixed-Effects Models." College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9546.

Full text

Abstract:

Thesis (Ph. D.) -- University of Maryland, College Park, 2009.
Thesis research directed by: Applied Mathematics & Statistics, and Scientific Computation Program. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

APA, Harvard, Vancouver, ISO, and other styles

9

Vong, Camille. "Model-Based Optimization of Clinical Trial Designs." Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-233445.

Full text

Abstract:

General attrition rates in drug development pipeline have been recognized as a necessity to shift gears towards new methodologies that allow earlier and correct decisions, and the optimal use of all information accrued throughout the process. The quantitative science of pharmacometrics using pharmacokinetic-pharmacodynamic models was identified as one of the strategies core to this renaissance. Coupled with Optimal Design (OD), they constitute together an attractive toolkit to usher more rapidly and successfully new agents to marketing approval. The general aim of this thesis was to investigate how the use of novel pharmacometric methodologies can improve the design and analysis of clinical trials within drug development. The implementation of a Monte-Carlo Mapped power method permitted to rapidly generate multiple hypotheses and to adequately compute the corresponding sample size within 1% of the time usually necessary in more traditional model-based power assessment. Allowing statistical inference across all data available and the integration of mechanistic interpretation of the models, the performance of this new methodology in proof-of-concept and dose-finding trials highlighted the possibility to reduce drastically the number of healthy volunteers and patients exposed to experimental drugs. This thesis furthermore addressed the benefits of OD in planning trials with bio analytical limits and toxicity constraints, through the development of novel optimality criteria that foremost pinpoint information and safety aspects. The use of these methodologies showed better estimation properties and robustness for the ensuing data analysis and reduced the number of patients exposed to severe toxicity by 7-fold. Finally, predictive tools for maximum tolerated dose selection in Phase I oncology trials were explored for a combination therapy characterized by main dose-limiting hematological toxicity. In this example, Bayesian and model-based approaches provided the incentive to a paradigm change away from the traditional rule-based “3+3” design algorithm. Throughout this thesis several examples have shown the possibility of streamlining clinical trials with more model-based design and analysis supports. Ultimately, efficient use of the data can elevate the probability of a successful trial and increase paramount ethical conduct.

APA, Harvard, Vancouver, ISO, and other styles

10

Barrowman, Nicholas J. "Nonlinear mixed effects models for meta-analysis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ57342.pdf.

Full text

APA, Harvard, Vancouver, ISO, and other styles

More sources

Books on the topic "Nonlinear mixed-effects model"

1

Linear and nonlinear models: Fixed effects, random effects, and mixed models. Berlin: Walter de Gruyter, 2006.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

2

Owen, Joel S. Introduction to population pharmacokinetic/pharmacodynamic analysis with nonlinear mixed effects models. Hoboken, New Jersey: Wiley, 2014.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

3

Owen, Joel S., and Jill Fiedler-Kelly. Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models. Hoboken, New Jersey: John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118784860.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Owen, Joel S., and Jill Fiedler-Kelly. Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models. Wiley & Sons, Incorporated, John, 2014.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

5

Owen, Joel S., and Jill Fiedler-Kelly. Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models. Wiley & Sons, Incorporated, John, 2014.

Find full text

APA, Harvard, Vancouver, ISO, and other styles

Book chapters on the topic "Nonlinear mixed-effects model"

1

Davidian, Marie. "Nonlinear Mixed Effects Models." In International Encyclopedia of Statistical Science, 947–50. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-04898-2_409.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Mehtätalo, Lauri, and Juha Lappi. "Nonlinear (Mixed-Effects) Models." In Biometry for Forestry and Environmental Data, 209–44. Boca Raton, FL : CRC Press, 2020. | Series: Chapman & Hall/CRC applied environmental statistics: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780429173462-7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Bonate, Peter L. "Nonlinear Mixed Effects Models: Theory." In Pharmacokinetic-Pharmacodynamic Modeling and Simulation, 233–301. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-9485-1_7.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Zhang, Heping. "Mixed-Effects Multivariate Adaptive Splines Models." In Nonlinear Estimation and Classification, 297–306. New York, NY: Springer New York, 2003. http://dx.doi.org/10.1007/978-0-387-21579-2_18.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Bonate, Peter L. "Nonlinear Mixed Effects Models: Practical Issues." In Pharmacokinetic-Pharmacodynamic Modeling and Simulation, 303–58. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-9485-1_8.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Bonate, Peter L. "Nonlinear Mixed Effects Models: Case Studies." In Pharmacokinetic-Pharmacodynamic Modeling and Simulation, 359–90. Boston, MA: Springer US, 2011. http://dx.doi.org/10.1007/978-1-4419-9485-1_9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Funatogawa, Ikuko, and Takashi Funatogawa. "Nonlinear Mixed Effects Models, Growth Curves, and Autoregressive Linear Mixed Effects Models." In Longitudinal Data Analysis, 99–117. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-0077-5_5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Demidenko, Eugene. "Asymptotic Properties of Nonlinear Mixed-Effects Models." In Modelling Longitudinal and Spatially Correlated Data, 49–62. New York, NY: Springer New York, 1997. http://dx.doi.org/10.1007/978-1-4612-0699-6_5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Luo, Xinchao, Lixing Zhu, Linglong Kong, and Hongtu Zhu. "Functional Nonlinear Mixed Effects Models for Longitudinal Image Data." In Lecture Notes in Computer Science, 794–805. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-19992-4_63.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

Karimi, Belhal, and Marc Lavielle. "Efficient Metropolis-Hastings Sampling for Nonlinear Mixed Effects Models." In Springer Proceedings in Mathematics & Statistics, 85–93. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-30611-3_9.

Full text

APA, Harvard, Vancouver, ISO, and other styles

Conference papers on the topic "Nonlinear mixed-effects model"

1

Denti, Paolo, Alessandra Bertoldo, Paolo Vicini, and Claudio Cobelli. "Identification of IVGTT minimal glucose model by nonlinear mixed-effects approaches." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.259555.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Denti, Paolo, Alessandra Bertoldo, Paolo Vicini, and Claudio Cobelli. "Identification of IVGTT minimal glucose model by nonlinear mixed-effects approaches." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4398588.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Largajolli, A., A. Bertoldo, and C. Cobelli. "Identification of the glucose minimal model by stochastic nonlinear-mixed effects methods." In 2012 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2012. http://dx.doi.org/10.1109/embc.2012.6347235.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Yu, Daojie, Xin Lin, Jianmin Wang, Weiqun Cui, Yuhua Guo, and Changfeng Zhang. "Nonlinear heating effects of stong wave longitudinal propagation in the ionosphere based on the model of mixed-atmosphere." In 2009 3rd IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications (MAPE). IEEE, 2009. http://dx.doi.org/10.1109/mape.2009.5355962.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Nijenhuis, Marijn, J. P. Meijaard, and Dannis M. Brouwer. "A Spatial Parametric Model for the Nonlinear Stiffness Characteristics of Flexure Strips." In ASME 2018 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/detc2018-86024.

Full text

Abstract:

The flexure strip is commonly used to provide support stiffness in flexure mechanisms for precision applications. While the flexure strip is often treated in a simplified form, e.g. by assuming planar deformation or linearized stiffness, the deformation in practice is spatial and sufficiently large that nonlinear effects due to the geometrical stiffness are significant. This paper presents an understandable analytical model for the nonlinear stiffness characteristics of flexure strips that deform spatially due to a general 3-D loading condition. This model provides closed-form expressions in a mixed stiffness and compliance matrix format that is tailored to flexure mechanism analysis. The effects of bending, elongation, and torsion deformation are taken into account. The geometrically nonlinear effects of the model are verified numerically. The approach for deriving closed-form solutions in a nonlinear context is detailed in this paper. Based on the Hellinger–Reissner variational principle, it can also be extended to the analysis of multi-flexure strip mechanisms. This is demonstrated with the case of a spatially deforming parallelogram flexure mechanism.

APA, Harvard, Vancouver, ISO, and other styles

6

Loizides, Charalambos, Achilleas Achilleos, Gian Domenico Iannetti, and Georgios D. Mitsis. "A mixed effects model framework for the assessment of nonlinear interactions in event-related potentials (ERPs) elicited by identical successive stimuli." In 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). IEEE, 2014. http://dx.doi.org/10.1109/embc.2014.6944634.

Full text

APA, Harvard, Vancouver, ISO, and other styles

7

Kameswaran, P. K., P. Sibanda, and A. S. N. Murti. "Viscous Dissipation and Soret Effects on Non-Darcy Mixed Convective Flow Considering Nanofluids." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-62131.

Full text

Abstract:

We investigate the steady boundary layer mixed convective flow over a horizontal impermeable wall embedded in a porous medium filled with a water-based nanofluid. The model used for the nanofluid incorporates the effects of the volume fraction parameter. The main objective of the present study is to investigate viscous dissipation and Soret effects on heat and mass transfer in a nanofluid containing Al2O3 and TiO2 nanoparticles. The temperature and concentrations at the wall were kept constant. A similarity transformation was used to obtain a system of nonlinear ordinary differential equations. The resulting nonlinear governing equations with associated boundary conditions were solved numerically using the Matlab bvp4c solver. The effects of viscous dissipation and the Soret parameter on dimensionless temperature, concentration, heat and mass transfer are presented graphically. It was observed that the heat transfer rate decreased with an increase in nanoparticle volume fraction. Comparison of current and previously published results (Lai and Kulaki [10], Arfin et al. [12]) showed a good agreement.

APA, Harvard, Vancouver, ISO, and other styles

8

Kogler, Helmut, Rudolf Scheidl, and Michael Ehrentraut. "A Simulation Model of a Hydraulic Buck Converter Based on a Mixed Time Frequency Domain Iteration." In ASME/BATH 2013 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/fpmc2013-4409.

Full text

Abstract:

Digital hydraulics is an opportunity to realize simple, robust, cheap and energy efficient hydraulic drives. In such systems digital on/off valves are used instead of proportional valves. Moreover, in hydraulic switching converters the valves are actuated within a few milliseconds, which create sharp pressure changes and, in turn, significant wave propagation effects in the pipe system. For a proper design of digital hydraulic systems a sound understanding of these effects is required to achieve the desired behavior of the switching drive system. In such converters, like the buck-, boost or boost-buck-converter, the inductance is one crucial component. It is realized by a simple pipe mainly for cost reasons. Furthermore, switching converters contain some components with nonlinear characteristics, like valves or accumulators, which prevent a comprehensive analysis in frequency domain. For a convenient analysis a qualified model of a hydraulic buck converter based on a mixed time frequency domain iteration is presented. Main parameters of this model are identified and wave propagation effects in the inductance pipe of the converter are investigated by simulation.

APA, Harvard, Vancouver, ISO, and other styles

9

Vinayan, Vimal, Spyros A. Kinnas, and Yi-Hsiang Yu. "Modeling of Flow Around FPSO Hull Sections Subject to Roll Motions: Effects of Nonlinear Boundary Conditions." In ASME 2005 24th International Conference on Offshore Mechanics and Arctic Engineering. ASMEDC, 2005. http://dx.doi.org/10.1115/omae2005-67142.

Full text

Abstract:

The paper presents the development of BEM (Boundary Element Method) and FVM (Finite Volume Method) based models for the analysis of the flow around 2-D FPSO hull-sections fitted with bilge keels and subject to forced roll motions. Through these models an attempt is made to gain an insight into the two important aspects of the flow: separation around bilge keels and the effect of the free-surface. The effect of the free-surface and the resulting wave-body interaction is studied using a 2-D BEM model coupled with a Mixed-Eulerian-Lagrangian (MEL) time marching scheme for the free-surface boundary conditions. The separation around the bilge keels and viscous aspects of the flow are studied using a FVM based 2-D Navier Stokes (2DNS) solver with linear free-surface boundary conditions. The primary aim of the BEM model is to investigate the effects of the linear and nonlinear boundary conditions on the predicted flow within the scope of the parameters of the FVM model.

APA, Harvard, Vancouver, ISO, and other styles

10

RAO, PODURI S. R. S., and NICHOLAS ZAINO. "NONLINEAR MIXED EFFECTS MODELS: RECENT DEVELOPMENTS." In Proceedings of Statistics 2001 Canada: The 4th Conference in Applied Statistics. PUBLISHED BY IMPERIAL COLLEGE PRESS AND DISTRIBUTED BY WORLD SCIENTIFIC PUBLISHING CO., 2002. http://dx.doi.org/10.1142/9781860949531_0021.

Full text

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!