Linear Mixed-Effects Models Using R

Engineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and

The chemostat is a basic piece of laboratory apparatus, yet it has occupied an increasingly central role in ecological studies. The ecological environment created by a chemostat is one of the few completely controlled experimental systems for testing microbial growth and competition. As a tool in biotechnology, the chemostat plays an important role in bioprocessing. This book presents the theory of the chemostat as a model for larger ecological problems such as food chains, competition along a gradient, competition in the presence of an inhibitor, and the effects of time varying inputs. Models which take account of size structure, variable yields, and diffusion are also considered. The basic phenomena are modelled and analysed using the dynamical systems approach. Directions for research and open problems are discussed. Six appendices provide an elementary description of the necessary mathematical tools. Teachers, researchers, and students in applied mathematics, chemical engineering a

In this book Gary Goertz examines how states interact with their environment and contexts, which are important in understanding international politics. He presents a philosophical, methodological and empirical discussion of three important contexts which affect decision makers: history, system structure, and international norms. The effects of these contexts are explored by viewing context in turn as cause, as changing meaning, and as a barrier. The book engages with the literature on structural realism and international regimes, and uses rational actor and diffusion models as theoretical references. A number of concrete studies are provided using these contextual tools, including oil nationalisation, USSR-East European relations, enduring rivalries, and decolonisation. These empirical examples illustrate the fruitfulness of the contextual approach to international politics.

The technique of allometry investigates the effects of size on such variables as food intake, energy requirements, growth rates and age at first reproduction. This book brings together much of what is known about the consequences of size and provides a new and mathematically rigorous framework within which many quantitative predictions are made and tested using published and unpublished data. Explanations are proposed for many previously unexplained phenomena such as why in some species females are thousands of times heavier than males, whereas in no species are males more than about eight times heavier than females. The models presented afford a synthesis of the effects of size and open up pathways for further theoretical investigation and experimental testing. Care has been taken to give verbal presentations of all the mathematical conclusions to ensure that the text is widely intelligible.

The technique of allometry investigates the effects of size on such variables as food intake, energy requirements, growth rates and age at first reproduction. This book brings together much of what is known about the consequences of size and provides a new and mathematically rigorous framework within which many quantitative predictions are made and tested using published and unpublished data. Explanations are proposed for many previously unexplained phenomena such as why in some species females are thousands of times heavier than males, whereas in no species are males more than about eight times heavier than females. The models presented afford a synthesis of the effects of size and open up pathways for further theoretical investigation and experimental testing. Care has been taken to give verbal presentations of all the mathematical conclusions to ensure that the text is widely intelligible.

Environmental external effects are evidence of the inability of market prices to reflect the interdependence of economic activities undertaken within a common environment. They are an essential - not a peripheral - feature of all market economics. This essay shows how external effects are produced by the interaction of the economy with its environment, using a classical mass-balance model. No matter how efficient the market may seem to be, the use of market prices to determine depletion and pollution decisions creates more problems than it solves. Far from sharing the stable or relatively stable equilibrium properties of most economic models, the market economy is shown to be forced by its environment through a seemingly chaotic sequence of states. Reliance on the market to accommodate each change of direction merely exaggerates the general instability of the system. The 'market solution' to environmental problems is shown to generate only increasing uncertainty, a progressive myopia,

Linear algebra and the study of matrix algorithms have become fundamental to the development of statistical models. Using a vector-space approach, this book provides an understanding of the major conc

Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish

In recent years there has been a wide interest in non-linear adaptive control using approximate models, either for tracking or regulation, and usually under the banner of neural network based control.

Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successfulIntuitive

This book provides practical applications of doubly classified models by using R syntax to generate the models. It also presents these models in symbolic tables so as to cater to those who are not mat

Spectrum(R) Addition for grade 1 provides focused practice in adding numbers through 100. Aligned to state standards, these activities include using visual models to represent problems, unknown number

Research on mixed models has been extensive over the most recent decade. This book differs from the authors' previous monographs on longitudinal data in that it focuses on mixed models of a linear, ge

From the very basics to linear models, this book provides a complete introduction to statistics, data analysis, and R for bioinformatics research and applications. It covers ANOVA, cluster analysis, v

This book provides the most comprehensive treatment to date of microeconometrics, the analysis of individual-level data on the economic behavior of individuals or firms using regression methods for cross section and panel data. The book is oriented to the practitioner. A basic understanding of the linear regression model with matrix algebra is assumed. The text can be used for a microeconometrics course, typically a second-year economics PhD course; for data-oriented applied microeconometrics field courses; and as a reference work for graduate students and applied researchers who wish to fill in gaps in their toolkit. Distinguishing features of the book include emphasis on nonlinear models and robust inference, simulation-based estimation, and problems of complex survey data. The book makes frequent use of numerical examples based on generated data to illustrate the key models and methods. More substantially, it systematically integrates into the text empirical illustrations based on s