Introduction to Mixed Modelling

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Introduction to Mixed Modelling. Beyond Regression and Analysis of Variance

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: “One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models…Each chapter is well-motivated by at least one carefully chosen example…demonstrating the broad applicability of mixed models in many different disciplines…most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic.”—Kerrie Nelson University of South Carolina, in American Statistician, 2007

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Introduction to Mixed Modelling. Beyond Regression and Analysis of Variance

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Introduction to Stochastic Differential Equations with Applications to Modelling in Biology and Finance

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Introduction to Population Pharmacokinetic / Pharmacodynamic Analysis with Nonlinear Mixed Effects Models

This book provides a user-friendly, hands-on introduction to the Nonlinear Mixed Effects Modeling (NONMEM) system, the most powerful tool for pharmacokinetic / pharmacodynamic analysis. • Introduces requisite background to using Nonlinear Mixed Effects Modeling (NONMEM), covering data requirements, model building and evaluation, and quality control aspects • Provides examples of nonlinear modeling concepts and estimation basics with discussion on the model building process and applications of empirical Bayesian estimates in the drug development environment • Includes detailed chapters on data set structure, developing control streams for modeling and simulation, model applications, interpretation of NONMEM output and results, and quality control • Has datasets, programming code, and practice exercises with solutions, available on a supplementary website

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Modelling Under Risk and Uncertainty. An Introduction to Statistical, Phenomenological and Computational Methods

Modelling has permeated virtually all areas of industrial, environmental, economic, bio-medical or civil engineering: yet the use of models for decision-making raises a number of issues to which this book is dedicated: How uncertain is my model ? Is it truly valuable to support decision-making ? What kind of decision can be truly supported and how can I handle residual uncertainty ? How much refined should the mathematical description be, given the true data limitations ? Could the uncertainty be reduced through more data, increased modeling investment or computational budget ? Should it be reduced now or later ? How robust is the analysis or the computational methods involved ? Should / could those methods be more robust ? Does it make sense to handle uncertainty, risk, lack of knowledge, variability or errors altogether ? How reasonable is the choice of probabilistic modeling for rare events ? How rare are the events to be considered ? How far does it make sense to handle extreme events and elaborate confidence figures ? Can I take advantage of expert / phenomenological knowledge to tighten the probabilistic figures ? Are there connex domains that could provide models or inspiration for my problem ? Written by a leader at the crossroads of industry, academia and engineering, and based on decades of multi-disciplinary field experience, Modelling Under Risk and Uncertainty gives a self-consistent introduction to the methods involved by any type of modeling development acknowledging the inevitable uncertainty and associated risks. It goes beyond the “black-box” view that some analysts, modelers, risk experts or statisticians develop on the underlying phenomenology of the environmental or industrial processes, without valuing enough their physical properties and inner modelling potential nor challenging the practical plausibility of mathematical hypotheses; conversely it is also to attract environmental or engineering modellers to better handle model confidence issues through finer statistical and risk analysis material taking advantage of advanced scientific computing, to face new regulations departing from deterministic design or support robust decision-making. Modelling Under Risk and Uncertainty: Addresses a concern of growing interest for large industries, environmentalists or analysts: robust modeling for decision-making in complex systems. Gives new insights into the peculiar mathematical and computational challenges generated by recent industrial safety or environmental control analysis for rare events. Implements decision theory choices differentiating or aggregating the dimensions of risk/aleatory and epistemic uncertainty through a consistent multi-disciplinary set of statistical estimation, physical modelling, robust computation and risk analysis. Provides an original review of the advanced inverse probabilistic approaches for model identification, calibration or data assimilation, key to digest fast-growing multi-physical data acquisition. Illustrated with one favourite pedagogical example crossing natural risk, engineering and economics, developed throughout the book to facilitate the reading and understanding. Supports Master/PhD-level course as well as advanced tutorials for professional training Analysts and researchers in numerical modeling, applied statistics, scientific computing, reliability, advanced engineering, natural risk or environmental science will benefit from this book.

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Approaches to Geo-mathematical Modelling

Geo-mathematical modelling: models from complexity science Sir Alan Wilson, Centre for Advanced Spatial Analysis, University College London Mathematical and computer models for a complexity science tool kit Geographical systems are characterised by locations, activities at locations, interactions between them and the infrastructures that carry these activities and flows. They can be described at a great variety of scales, from individuals and organisations to countries. Our understanding, often partial, of these entities, and in many cases this understanding is represented in theories and associated mathematical models. In this book, the main examples are models that represent elements of the global system covering such topics as trade, migration, security and development aid together with examples at finer scales. This provides an effective toolkit that can not only be applied to global systems, but more widely in the modelling of complex systems. All complex systems involve nonlinearities involving path dependence and the possibility of phase changes and this makes the mathematical aspects particularly interesting. It is through these mechanisms that new structures can be seen to ‘emerge’, and hence the current notion of ‘emergent behaviour’. The range of models demonstrated include account-based models and biproportional fitting, structural dynamics, space-time statistical analysis, real-time response models, Lotka-Volterra models representing ‘war’, agent-based models, epidemiology and reaction-diffusion approaches, game theory, network models and finally, integrated models. Geo-mathematical modelling: Presents mathematical models with spatial dimensions. Provides representations of path dependence and phase changes. Illustrates complexity science using models of trade, migration, security and development aid. Demonstrates how generic models from the complexity science tool kit can each be applied in a variety of situations This book is for practitioners and researchers in applied mathematics, geography, economics, and interdisciplinary fields such as regional science and complexity science. It can also be used as the basis of a modelling course for postgraduate students.

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Introduction to Sociology

This book provides an invaluable introduction to his historical and conceptual engagement with sociology.

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Introduction to Desalination

INTRODUCTION TO DESALINATION

Explore the principles, methods, and applications of modern desalination processes

Introduction to Desalination: Principles, Processes, and Calculations delivers a comprehensive and robust exploration of desalination highlighted with numerous illustrative examples and calculations.

The book is divided into three sections, the first of which offers an introduction to the topic that includes chapters covering global water scarcity and the need for “new water.” The second section discusses the desalination process, including evaporation, reverse osmosis, crystallization, hybrid systems, and other potable water processes. The final part covers topics that include water conservation, environmental considerations of desalination, economic impacts of desalination, optimization, ethics, and the future of desalination.

The book also includes:

A comprehensive introduction to desalination, including discussions of engineering principles, the physical, chemical, and biological properties of water, and water chemistry
An extensive engineering analysis of the various desalination processes
Practical discussions of miscellaneous desalination topics, including the environmental and economic effects of the technology

Perfect for process, chemical, mechanical, environmental, and civil engineers, Introduction to Desalination: Principles, Processes, and Calculations is also a valuable resource for materials scientists, operators, and technicians working in the field.

Цена 16066 руб.

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Introduction to Pragmatics

Introduction to Pragmatics guides students through traditional and new approaches in the field, focusing particularly on phenomena at the elusive semantics/pragmatics boundary to explore the role of context in linguistic communication. Offers students an accessible introduction and an up-to-date survey of the field, encompassing both established and new approaches to pragmatics Addresses the traditional range of topics – such as implicature, reference, presupposition, and speech acts – as well as newer areas of research, including neo-Gricean theories, Relevance Theory, information structure, inference, and dynamic approaches to meaning Explores the relationship and boundaries between semantics and pragmatics Ideal for students coming to pragmatics for the first time

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A Concrete Approach to Mathematical Modelling

WILEY-INTERSCIENCE PAPERBACK SERIES The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. « . . . [a] treasure house of material for students and teachers alike . . . can be dipped into regularly for inspiration and ideas. It deserves to become a classic.» —London Times Higher Education Supplement «The author succeeds in his goal of serving the needs of the undergraduate population who want to see mathematics in action, and the mathematics used is extensive and provoking.» —SIAM Review «Each chapter discusses a wealth of examples ranging from old standards . . . to novelty . . . each model is developed critically, analyzed critically, and assessed critically.» —Mathematical Reviews A Concrete Approach to Mathematical Modelling provides in-depth and systematic coverage of the art and science of mathematical modelling. Dr. Mesterton-Gibbons shows how the modelling process works and includes fascinating examples from virtually every realm of human, machine, natural, and cosmic activity. Various models are found throughout the book, including how to determine how fast cars drive through a tunnel, how many workers industry should employ, the length of a supermarket checkout line, and more. With detailed explanations, exercises, and examples demonstrating real-life applications in diverse fields, this book is the ultimate guide for students and professionals in the social sciences, life sciences, engineering, statistics, economics, politics, business and management sciences, and every other discipline in which mathematical modelling plays a role.

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Цвета для малышей

Вашему вниманию предлагается книга Цвета для малышей

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Оздоровительные технологии физического воспитания детей младшего школьного возраста. Учебное пособие

Учебное пособие посвящено вопросам организации физического воспитания детей младшего школьного возраста. В нем показаны особенности программного обеспечения физического воспитания в России и за рубежом, рассмотрены программы физического воспитания детей, отнесенных к специальной медицинской группе, а также изложена теоретико-методологическая концепция оздоровительного физического воспитания учащихся младших классов общеобразовательных школ.

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Инновационные предприятия в вузах: вопросы интеграции с реальным сектором экономики 2-е изд., испр.

В книге изложены вопросы востребованности научной продукции, разрабатываемой образовательными учреждениями. В ней показано становление малых инновационных предприятий университетов, результативность взаимодействия вузов, НИИ и производственных компаний в сфере науки и инноваций, а также дан прогноз в сфере интеграции вузовской науки и инноваций высокотехнологичных компаний. . .

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Цвета. Уроки-картинки

"Уроки-картинки" помогают легко усвоить базовые понятия, расширяют словарный запас, тренируют память, внимание и логику, радуют ребёнка и родителей.

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Кто что ест. Первые слова

Серия развивающих книжек знакомит ребенка с базовыми понятиями, расширяет его словарный запас, способствует формированию логического мышления. Обучение построено в форме игры: перелистывая разрезанные посредине страницы, ребенок должен на правой половинке найти парную картинку к левой. .

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