The Theory of Dispersion Models

The Theory of Dispersion Models PDF Author: Bent Jorgensen
Publisher: CRC Press
ISBN: 9780412997112
Category : Mathematics
Languages : en
Pages : 264

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Book Description
The theory of dispersion models straddles both statistics and probability, and involves an encyclopedic collection of tools, such as exponential families, asymptotic theory, stochastic processes, Tauber theory, infinite divisibility, and stable distributions. The Theory of Dispersion Models introduces the reader to these models, which serve as error distributions for generalized linear models, and looks at their applications within this context.

The Theory of Dispersion Models

The Theory of Dispersion Models PDF Author: Bent Jorgensen
Publisher: CRC Press
ISBN: 9780412997112
Category : Mathematics
Languages : en
Pages : 264

Get Book Here

Book Description
The theory of dispersion models straddles both statistics and probability, and involves an encyclopedic collection of tools, such as exponential families, asymptotic theory, stochastic processes, Tauber theory, infinite divisibility, and stable distributions. The Theory of Dispersion Models introduces the reader to these models, which serve as error distributions for generalized linear models, and looks at their applications within this context.

Air Dispersion Modeling

Air Dispersion Modeling PDF Author: Alex De Visscher
Publisher: John Wiley & Sons
ISBN: 1118723104
Category : Technology & Engineering
Languages : en
Pages : 526

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Book Description
A single reference to all aspects of contemporary air dispersion modeling The practice of air dispersion modeling has changed dramatically in recent years, in large part due to new EPA regulations. Current with the EPA's 40 CFR Part 51, this book serves as a complete reference to both the science and contemporary practice of air dispersion modeling. Throughout the book, author Alex De Visscher guides readers through complex calculations, equation by equation, helping them understand precisely how air dispersion models work, including such popular models as the EPA's AERMOD and CALPUFF. Air Dispersion Modeling begins with a primer that enables readers to quickly grasp basic principles by developing their own air dispersion model. Next, the book offers everything readers need to work with air dispersion models and accurately interpret their results, including: Full chapter dedicated to the meteorological basis of air dispersion Examples throughout the book illustrating how theory translates into practice Extensive discussions of Gaussian, Lagrangian, and Eulerian air dispersion modeling Detailed descriptions of the AERMOD and CALPUFF model formulations This book also includes access to a website with Microsoft Excel and MATLAB files that contain examples of air dispersion model calculations. Readers can work with these examples to perform their own calculations. With its comprehensive and up-to-date coverage, Air Dispersion Modeling is recommended for environmental engineers and meteorologists who need to perform and evaluate environmental impact assessments. The book's many examples and step-by-step instructions also make it ideal as a textbook for students in the fields of environmental engineering, meteorology, chemical engineering, and environmental sciences.

Atmospheric Dispersion Modelling

Atmospheric Dispersion Modelling PDF Author: Rod Barratt
Publisher: Routledge
ISBN: 1134194978
Category : Political Science
Languages : en
Pages : 265

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Book Description
To comply with legal and other standards, businesses and regulators are increasingly required to make decisions based on risk assessments of the potential effects of their activities on the environment. Atmospheric dispersion modelling is a cost-effective method, allowing various scenarios to be explored before expensive investment takes place. This guide offers advice on this environmental management tool. Unlike much of the previous literature, it doesn't focus excessively on the mathematical theory behind the modelling or on modelling for specific regulatory purposes. Instead, it offers an understanding of the background to the methodologies, providing exercises to develop the skills to carry these out and including examples of the use of commercially available models to enable the reader to assess the results of modelling for risk assessment.

Air Pollution Modeling and Its Application XII

Air Pollution Modeling and Its Application XII PDF Author: Sven-Erik Gryning
Publisher: Springer Science & Business Media
ISBN: 1475791283
Category : Science
Languages : en
Pages : 739

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Book Description
Proceedings of the Twenty-Second NATO/CCMS International Technical Meeting held in Clermont-Ferrand, France, June 2-6, 1997

Correlated Data Analysis: Modeling, Analytics, and Applications

Correlated Data Analysis: Modeling, Analytics, and Applications PDF Author: Peter X. -K. Song
Publisher: Springer Science & Business Media
ISBN: 038771393X
Category : Mathematics
Languages : en
Pages : 352

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Book Description
This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Air Pollution Modeling

Air Pollution Modeling PDF Author: P. Zannetti
Publisher: Springer Science & Business Media
ISBN: 147574465X
Category : Science
Languages : en
Pages : 448

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Book Description
Finishing this book is giving me a mixture of relief, satisfaction and frus tration. Relief, for the completion of a project that has taken too many of my evenings and weekends and that, in the last several months, has become almost an obsession. Satisfaction, for the optimistic feeling that this book, in spite of its many shortcomings and imbalances, will be of some help to the air pollution scientific community. Frustration, for the impossibility of incorporating newly available material that would require another major review of several key chap ters - an effort that is currently beyond my energies but not beyond my desires. The first canovaccio of this book came out in 1980 when I was invited by Computational Mechanics in the United Kingdom to give my first Air Pollution Modeling course. The course material, in the form of transparencies, expanded, year after year, thus providing a growing working basis. In 1985, the ECC Joint Research Center in Ispra, Italy, asked me to prepare a critical survey of mathe matical models of atmospheric pollution, transport and deposition. This support gave me the opportunity to prepare a sort of "first draft" of the book, which I expanded in the following years.

Information and Exponential Families

Information and Exponential Families PDF Author: O. Barndorff-Nielsen
Publisher: John Wiley & Sons
ISBN: 1118857372
Category : Mathematics
Languages : en
Pages : 248

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Book Description
First published by Wiley in 1978, this book is being re-issued with a new Preface by the author. The roots of the book lie in the writings of RA Fisher both as concerns results and the general stance to statistical science, and this stance was the determining factor in the author's selection of topics. His treatise brings together results on aspects of statistical information, notably concerning likelihood functions, plausibility functions, ancillarity, and sufficiency, and on exponential families of probability distributions.

Generalized Linear Models

Generalized Linear Models PDF Author: P. McCullagh
Publisher: Routledge
ISBN: 1351445847
Category : Mathematics
Languages : en
Pages : 536

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Book Description
The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and ot

Selected Works of E. L. Lehmann

Selected Works of E. L. Lehmann PDF Author: Javier Rojo
Publisher: Springer Science & Business Media
ISBN: 1461414113
Category : Mathematics
Languages : en
Pages : 1103

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Book Description
These volumes present a selection of Erich L. Lehmann’s monumental contributions to Statistics. These works are multifaceted. His early work included fundamental contributions to hypothesis testing, theory of point estimation, and more generally to decision theory. His work in Nonparametric Statistics was groundbreaking. His fundamental contributions in this area include results that came to assuage the anxiety of statisticians that were skeptical of nonparametric methodologies, and his work on concepts of dependence has created a large literature. The two volumes are divided into chapters of related works. Invited contributors have critiqued the papers in each chapter, and the reprinted group of papers follows each commentary. A complete bibliography that contains links to recorded talks by Erich Lehmann – and which are freely accessible to the public – and a list of Ph.D. students are also included. These volumes belong in every statistician’s personal collection and are a required holding for any institutional library.

Generalized Linear Models With Examples in R

Generalized Linear Models With Examples in R PDF Author: Peter K. Dunn
Publisher: Springer
ISBN: 1441901183
Category : Mathematics
Languages : en
Pages : 573

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Book Description
This textbook presents an introduction to generalized linear models, complete with real-world data sets and practice problems, making it applicable for both beginning and advanced students of applied statistics. Generalized linear models (GLMs) are powerful tools in applied statistics that extend the ideas of multiple linear regression and analysis of variance to include response variables that are not normally distributed. As such, GLMs can model a wide variety of data types including counts, proportions, and binary outcomes or positive quantities. The book is designed with the student in mind, making it suitable for self-study or a structured course. Beginning with an introduction to linear regression, the book also devotes time to advanced topics not typically included in introductory textbooks. It features chapter introductions and summaries, clear examples, and many practice problems, all carefully designed to balance theory and practice. The text also provides a working knowledge of applied statistical practice through the extensive use of R, which is integrated into the text. Other features include: • Advanced topics such as power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, small-dispersion asymptotics, and randomized quantile residuals • Nearly 100 data sets in the companion R package GLMsData • Examples that are cross-referenced to the companion data set, allowing readers to load the data and follow the analysis in their own R session