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Dissertations / Theses on the topic 'Mixed model'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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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.

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2

Waterman, Megan Janet Tuttle. "Linear Mixed Model Robust Regression." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/27708.

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Mixed models are powerful tools for the analysis of clustered data and many extensions of the classical linear mixed model with normally distributed response have been established. As with all parametric models, correctness of the assumed model is critical for the validity of the ensuing inference. Model robust regression techniques predict mean response as a convex combination of a parametric and a nonparametric model fit to the data. It is a semiparametric method by which incompletely or incorrectly specified parametric models can be improved through adding an appropriate amount of a nonpara

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3

Overstall, Antony Marshall. "Default Bayesian model determination for generalised linear mixed models." Thesis, University of Southampton, 2010. https://eprints.soton.ac.uk/170229/.

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In this thesis, an automatic, default, fully Bayesian model determination strategy for GLMMs is considered. This strategy must address the two key issues of default prior specification and computation. Default prior distributions for the model parameters, that are based on a unit information concept, are proposed. A two-phase computational strategy, that uses a reversible jump algorithm and implementation of bridge sampling, is also proposed. This strategy is applied to four examples throughout this thesis.

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4

Sima, Adam. "Accounting for Model Uncertainty in Linear Mixed-Effects Models." VCU Scholars Compass, 2013. http://scholarscompass.vcu.edu/etd/2950.

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Standard statistical decision-making tools, such as inference, confidence intervals and forecasting, are contingent on the assumption that the statistical model used in the analysis is the true model. In linear mixed-effect models, ignoring model uncertainty results in an underestimation of the residual variance, contributing to hypothesis tests that demonstrate larger than nominal Type-I errors and confidence intervals with smaller than nominal coverage probabilities. A novel utilization of the generalized degrees of freedom developed by Zhang et al. (2012) is used to adjust the estimate of t

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5

Li, Qie. "A Bayesian Hierarchical Model for Multiple Comparisons in Mixed Models." Bowling Green State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1342530994.

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6

Prosser, Robert James. "Robustness of multivariate mixed model ANOVA." Thesis, University of British Columbia, 1985. http://hdl.handle.net/2429/25511.

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In experimental or quasi-experimental studies in which a repeated measures design is used, it is common to obtain scores on several dependent variables on each measurement occasion. Multivariate mixed model (MMM) analysis of variance (Thomas, 1983) is a recently developed alternative to the MANOVA procedure (Bock, 1975; Timm, 1980) for testing multivariate hypotheses concerning effects of a repeated factor (called occasions in this study) and interaction between repeated and non-repeated factors (termed group-by-occasion interaction here). If a condition derived by Thomas (1983), multivariate

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7

Jensen, Willis Aaron. "Profile Monitoring for Mixed Model Data." Diss., Virginia Tech, 2006. http://hdl.handle.net/10919/27054.

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The initial portion of this research focuses on appropriate parameter estimators within a general context of multivariate quality control. The goal of Phase I analysis of multivariate quality control data is to identify multivariate outliers and step changes so that the estimated control limits are sufficiently accurate for Phase II monitoring. High breakdown estimation methods based on the minimum volume ellipsoid (MVE) or the minimum covariance determinant (MCD) are well suited to detecting multivariate outliers in data. Because of the inherent difficulties in computation many algorithms hav

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8

Wenren, Cheng. "Mixed Model Selection Based on the Conceptual Predictive Statistic." Bowling Green State University / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1403735738.

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9

Pan, Juming. "Adaptive LASSO For Mixed Model Selection via Profile Log-Likelihood." Bowling Green State University / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1466633921.

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10

Yu, Fu. "On statistical analysis of vehicle time-headways using mixed distribution models." Thesis, University of Dundee, 2014. https://discovery.dundee.ac.uk/en/studentTheses/d101df63-b7db-45b6-8a03-365b64345e6b.

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For decades, vehicle time-headway distribution models have been studied by many researchers and traffic engineers. A good time-headway model can be beneficial to traffic studies and management in many aspects; e.g. with a better understanding of road traffic patterns and road user behaviour, the researchers or engineers can give better estimations and predictions under certain road traffic conditions and hence make better decisions on traffic management and control. The models also help us to implement high-quality microscopic traffic simulation studies to seek good solutions to traffic proble

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11

Ucar, Emre. "Mixed-model Two-sided Assembly Line Balancing." Master's thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611688/index.pdf.

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In this study we focus on two-sided mixed-model assembly line balancing type-I problem. There is a production target for a fixed time horizon and the objective is to produce this amount with the minimum level of workforce. A mathematical model is developed to solve this problem in an optimal manner. For large scale problems, the mathematical model fails to give the optimal solution within reasonable computational times. Thus, a heuristic approach based on threshold accepting algorithm is presented. Both the mathematical model and the heuristic approach are executed to solve several example pro

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12

Cronje, Tanita. "A mixed model approach to conjoint analysis." Diss., University of Pretoria, 2014. http://hdl.handle.net/2263/79776.

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In this decision-driven era, it has become vital for modelers to efficiently model consumer choices and preferences (from a marketing perspective for instance). Conjoint analysis is a known method which has been used to perform such analyses. A mixed effects model is proposed to perform a conjoint analysis with normal responses, illustrated by an application of modeling respondent’s preferences to different industrial detergents. The proposed model allows for predicting how observed attributes (which describes a product in terms of its characteristics and features) of decision makers and

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13

Alabiso, Audry. "Linear Mixed Model Selection by Partial Correlation." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1587142724497829.

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14

Dixon, Cheryl Annette. "Power Analysis for the Mixed Linear Model." VCU Scholars Compass, 1996. http://scholarscompass.vcu.edu/etd/4525.

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Power analysis is becoming standard in inference based research proposals and is used to support the proposed design and sample size. The choice of an appropriate power analysis depends on the choice of the research question, measurement procedures, design, and analysis plan. The "best" power analysis, however, will have many features of a sound data analysis. First, it addresses the study hypothesis, and second, it yields a credible answer. Power calculations for standard statistical hypotheses based on normal theory have been defined for t-tests through the univariate and multivariate genera

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15

Schwardt, Ludwig. "Efficient Mixed-Order Hidden Markov Model Inference." Thesis, Link to the online version, 2007. http://hdl.handle.net/10019/709.

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16

Abraham, Anita Ann Edwards Lloyd J. "Model selection methods in the linear mixed model for longitudinal data." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2008. http://dc.lib.unc.edu/u?/etd,1859.

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Thesis (DrPH)--University of North Carolina at Chapel Hill, 2008.<br>Title from electronic title page (viewed Dec. 11, 2008). "... in partial fulfillment of the requirements for the degree of Doctor of Public Health in the Department of Biostatistics, School of Public Health." Discipline: Biostatistics; Department/School: Public Health.

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17

Gory, Jeffrey J. "Marginally Interpretable Generalized Linear Mixed Models." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu1497966698387606.

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18

Yousef, Mohammed A. "Two-Stage SCAD Lasso for Linear Mixed Model Selection." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1558431514460879.

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19

Yam, Ho-kwan, and 任浩君. "On a topic of generalized linear mixed models and stochastic volatility model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B29913342.

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20

Kneib, Thomas. "Mixed model based inference in structured additive regression." [S.l.] : [s.n.], 2005. http://edoc.ub.uni-muenchen.de/archive/00005011.

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21

Kneib, Thomas. "Mixed model based inference in structured additive regression." Diss., lmu, 2006. http://nbn-resolving.de/urn:nbn:de:bvb:19-50112.

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22

Zhu, Xiaohong. "Numerical methods for a mixed Stokes-Darcy model /." View abstract or full-text, 2007. http://library.ust.hk/cgi/db/thesis.pl?MATH%202007%20ZHU.

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23

Beckler, Robert Kendall. "Polynuclear metal complexes as model mixed oxide catalysts." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/11897.

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24

Tang, On-yee, and 鄧安怡. "Estimation for generalized linear mixed model via multipleimputations." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B30687652.

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25

Welham, Suzanne Jane. "Smoothing spline methods within the mixed model framework." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2005. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.425673.

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26

Lindkvist, Oskar. "Model Adaptation of a Mixed Flow Turbofan Engine." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-80667.

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Gas turbine performance models are usually created in an object oriented manner, where different standard components are connected to form the complete model. The characteristics of these components are often represented by component maps and empirical correlations. However, engine specific component characteristics are seldom available to anyone outside of the manufacturers. It is therefore very common for researchers to use publicly accessible or generic component maps instead. But in order to reduce prediction errors the maps have to be modified to fit any specific engine. This thesis work

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27

Cheldelin, Brent. "Design for mixed model production of complex products /." May be available electronically:, 2007. http://proquest.umi.com/login?COPT=REJTPTU1MTUmSU5UPTAmVkVSPTI=&clientId=12498.

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28

Wang, Mengyu. "Model-based Optimisation of Mixed Refrigerant LNG Processes." Thesis, The University of Sydney, 2017. http://hdl.handle.net/2123/17387.

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Natural gas liquefaction processes are energy and cost intensive. This thesis pursues the optimisation of propane precooled mixed refrigerant (C3MR) processes considering variations in upstream gas well conditions, in order to maximise gas well life. Four objective functions were selected for the design optimisation of the C3MR and dual mixed refrigerant (DMR) processes: 1) total shaft work (W), 2) total capital investment, 3) total annualised cost, and 4) total capital cost of both compressors and main cryogenic heat exchanger (MCHE). Optimisation results show that objective function 4 is mor

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29

Jesser, Alexander. "Mixed signal circuit verification using symbolic model checking techniques." München Verl. Dr. Hut, 2008. http://d-nb.info/992162858/04.

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30

Lee, Yi-Ching. "An Approach to Estimation and Selection in Linear Mixed Models with Missing Data." Bowling Green State University / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1562754262770979.

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31

Wu, Hongqian. "Proportional likelihood ratio mixed model for longitudinal discrete data." Diss., University of Iowa, 2016. https://ir.uiowa.edu/etd/2296.

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A semiparametric proportional likelihood ratio model was proposed by Luo and Tsai (2012) which is suitable for modeling a nonlinear monotonic relationship between the response variable and a covariate. Extending the generalized linear model, this model leaves the probability distribution unspecified but estimates it from the data. In this thesis, we propose to extend this model into analyzing the longitudinal data by incorporating random effects into the linear predictor. By using this model as the conditional density of the response variable given the random effects, we present a maximum like

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32

Wang, Jun. "Selecting the Best Linear Mixed Model Using Predictive Approaches." Diss., CLICK HERE for online access, 2007. http://contentdm.lib.byu.edu/ETD/image/etd1697.pdf.

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33

Burdett, Robert. "Sequencing and scheduling theory for mixed-model multi-stage assembly environment." Thesis, Queensland University of Technology, 2001.

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34

Tang, On-yee. "Estimation for generalized linear mixed model via multiple imputations." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B30687652.

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35

Holth, Erik. "Model Predictive Control of mixed solar and electric heating." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9106.

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<p>In this report we will model a heat system consisting of a heat storage tank and an application. The heat storage tank is supplied by a heating element and heated water from a solar collector. The main objective of the heat system is to mainatian a reference temperature in the application (a house). Weather forecasts will be used as weather data affecting the heat system. We will assume that the weather forecasts and the actual weather will be the same. The heat sytem will consist of simplified nonlinear differential equations and be controlled by a model predictive controller (mpc). The mp

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36

Kliegl, Reinhold, Michael E. J. Masson, and Eike M. Richter. "A linear mixed model analysis of masked repetition priming." Universität Potsdam, 2009. http://opus.kobv.de/ubp/volltexte/2011/5707/.

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We examined individual differences in masked repetition priming by re-analyzing item-level response-time (RT) data from three experiments. Using a linear mixed model (LMM) with subjects and items specified as crossed random factors, the originally reported priming and word-frequency effects were recovered. In the same LMM, we estimated parameters describing the distributions of these effects across subjects. Subjects’ frequency and priming effects correlated positively with each other and negatively with mean RT. These correlation estimates, however, emerged only with a reciprocal transformati

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37

Lan, Lan. "Variable Selection in Linear Mixed Model for Longitudinal Data." NCSU, 2006. http://www.lib.ncsu.edu/theses/available/etd-05172006-211924/.

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Fan and Li (JASA, 2001) proposed a family of variable selection procedures for certain parametric models via a nonconcave penalized likelihood approach, where significant variable selection and parameter estimation were done simultaneously, and the procedures were shown to have the oracle property. In this presentation, we extend the nonconcave penalized likelihood approach to linear mixed models for longitudinal data. Two new approaches are proposed to select significant covariates and estimate fixed effect parameters and variance components. In particular, we show the new approaches also pos

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38

Hone, David M. "Time and space resolution and mixed layer model accuracy." Monterey, California. Naval Postgraduate School, 1997. http://hdl.handle.net/10945/9080.

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The oceanic turbulent boundary layer is a critical region to understand for oceanic and atmospheric prediction. This thesis answers two fundamental questions: (1) what is the response of the ocean mixed layer system to transient forcing at the air sea surface? (2) what is the necessary time and space resolution in an ocean mixed layer model to resolve important transient responses? Beginning with replication of de Szoeke and Rhines' work, additional physical processes were added to include more realistic viscous dissipation and anisotropy in the three-dimensional turbulent kinetic energy (TKE)

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39

Jacobs, Katrien. "Illumination for mixed reality of complex-to-model scenes." Thesis, University College London (University of London), 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440451.

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40

Al-Shaikh, Enas. "Longitudinal Regression Analysis Using Varying Coefficient Mixed Effect Model." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543464.

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41

Atutey, Olivia Abena. "Linear Mixed Model Selection via Minimum Approximated Information Criterion." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1594910831256966.

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42

Baumann, Frank Stephan. "Oxygen reduction kinetics on mixed conducting SOFC model cathodes." [S.l. : s.n.], 2006. http://nbn-resolving.de/urn:nbn:de:bsz:93-opus-27056.

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43

Le, Chenechal Morgan. "Awareness Model for Asymmetric Remote Collaboration in Mixed Reality." Thesis, Rennes, INSA, 2016. http://www.theses.fr/2016ISAR0006/document.

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Etre capable de collaborer à distance avec d'autres personnes peut fournir de précieuses capacités pour effectuer des tâches qui ont besoin de plusieurs utilisateurs pour être accomplies. De plus, les technologies de Réalité Mixte (RM) sont des outils intéressants pour développer de nouveaux types d'applications offrant des interactions et des possibilités de perception plus naturelles comparées aux systèmes classiques. Dans cette thèse, nous proposons d'améliorer la collaboration distante en utilisant ces technologies de RM qui profitent de nos capacités naturelles à effectuer des tâches en e

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44

Codd, Casey. "A Review and Comparison of Models and Estimation Methods for Multivariate Longitudinal Data of Mixed Scale Type." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1398686513.

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45

Greenaway, Mark Jonathan. "Numerically Stable Approximate Bayesian Methods for Generalized Linear Mixed Models and Linear Model Selection." Thesis, The University of Sydney, 2019. http://hdl.handle.net/2123/20233.

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Approximate Bayesian inference methods offer methodology for fitting Bayesian models as fast alternatives to Markov Chain Monte Carlo methods that sometimes have only a slight loss of accuracy. In this thesis, we consider variable selection for linear models, and zero inflated mixed models. Variable selection for linear regression models are ubiquitous in applied statistics. We use the popular g-prior (Zellner, 1986) for model selection of linear models with normal priors where g is a prior hyperparameter. We derive exact expressions for the model selection Bayes Factors in terms of special f

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46

Alves, Victor César Costa [UNESP]. "Painlevé Integrability and mixed P_III-P_V system solutions." Universidade Estadual Paulista (UNESP), 2017. http://hdl.handle.net/11449/149963.

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Submitted by VICTOR CESAR COSTA ALVES null (victorc@ift.unesp.br) on 2017-03-24T17:06:35Z No. of bitstreams: 1 document.pdf: 511663 bytes, checksum: 1bf722030b47e34e0031fc461efd9f67 (MD5)<br>Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-03-24T20:35:37Z (GMT) No. of bitstreams: 1 alves_vcc_me_ift.pdf: 511663 bytes, checksum: 1bf722030b47e34e0031fc461efd9f67 (MD5)<br>Made available in DSpace on 2017-03-24T20:35:37Z (GMT). No. of bitstreams: 1 alves_vcc_me_ift.pdf: 511663 bytes, checksum: 1bf722030b47e34e0031fc461efd9f67 (MD5) Previous issue date: 2017-02-

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47

Casale, Francesco Paolo. "Multivariate linear mixed models for statistical genetics." Thesis, University of Cambridge, 2016. https://www.repository.cam.ac.uk/handle/1810/267465.

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In the last decade, genome-wide association studies have helped to advance our understanding of the genetic architecture of many important traits, including diseases. However, the statistical analysis of genotype-phenotype associations remains challenging due to multiple factors. First, many traits have polygenic architectures, which means that they are controlled by a large number of variants with small individual effects. Second, as increasingly deep phenotype data are being generated there is a need for multivariate analysis approaches to leverage multiple related phenotypes while retaining

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Alves, Victor César Costa. "Painlevé Integrability and mixed P_III-P_V system solutions /." São Paulo, 2017. http://hdl.handle.net/11449/149963.

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Orientador: Abraham Hirsz Zimerman<br>Abstract: The current work aims at applications of mathematical methods of Painlevé integrability in physics, on the other side it also approaches the integrable hierarchies formalism and the 2M-bose model where differential equations methods are used as well as a method for solutions using Padé approximants.<br>Resumo: O presente trabalho trata de um abordagem de aplicações em física dos métodos matemáticos de integrabilidade de Painlevé, por outro lado também aborda o formalismo de hierarquias integráveis e o modelo de 2M-bosons onde são usados métodos d

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49

Båtelsson, Niklas, and Simon Alfredsson. "Assembly system design - : Case study of a mixed model production." Thesis, KTH, Industriell produktion, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-103276.

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The report, which is a part of the course "MG202X Examensarbete", has been written for the institution Industrial Production at the Royal Institute of Technology (KTH) with guidance from Antonio Maffei. The work has been focused on creating an assembly system at a production facility for Schneider Electric in Nyköping. The Authors has divided the report into a literature review containing Lean production and assembly systems, an analysis of the initial state and a solution. The literature review presents three separate parts which creates the framework of our analysis. The first part regards a

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50

Nordsveen, Espen T. "Mixed Integer Model Predictive Control of Multiple Shale Gas Wells." Thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for teknisk kybernetikk, 2012. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-18400.

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Horizontal wells with multistage hydraulic fracturing are today the most important drilling technology for shale gas extraction. Considered unprofitable before, the production has now become economically profitable due to advances in technology. Shales main characteristics is its low permeability, making the gas challenging and expensive to extract. Hydraulic fracturing stimulates the wells by creating additional conductivity, making the gas flows from storage pores to the well. This flow only possible in a short time scale, and states the need for multistage fracturing. Shale gas flow theref

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