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Spatial Analysis Along Networks

Author: Atsuyuki Okabe
Publisher: John Wiley & Sons
ISBN: 1119967767
Size: 77.22 MB
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In the real world, there are numerous and various events that occur on and alongside networks, including the occurrence of traffic accidents on highways, the location of stores alongside roads, the incidence of crime on streets and the contamination along rivers. In order to carry out analyses of those events, the researcher needs to be familiar with a range of specific techniques. Spatial Analysis Along Networks provides a practical guide to the necessary statistical techniques and their computational implementation. Each chapter illustrates a specific technique, from Stochastic Point Processes on a Network and Network Voronoi Diagrams, to Network K-function and Point Density Estimation Methods, and the Network Huff Model. The authors also discuss and illustrate the undertaking of the statistical tests described in a Geographical Information System (GIS) environment as well as demonstrating the user-friendly free software package SANET. Spatial Analysis Along Networks: Presents a much-needed practical guide to statistical spatial analysis of events on and alongside a network, in a logical, user-friendly order. Introduces the preliminary methods involved, before detailing the advanced, computational methods, enabling the readers a complete understanding of the advanced topics. Dedicates a separate chapter to each of the major techniques involved. Demonstrates the practicalities of undertaking the tests described in the book, using a GIS. Is supported by a supplementary website, providing readers with a link to the free software package SANET, so they can execute the statistical methods described in the book. Students and researchers studying spatial statistics, spatial analysis, geography, GIS, OR, traffic accident analysis, criminology, retail marketing, facility management and ecology will benefit from this book.

Spatial And Temporal Databases

Author: Mario Nascimento
Publisher: Springer
ISBN: 3642402356
Size: 36.31 MB
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This book constitutes the refereed proceedings of the 13th International Symposium on Spatial and Temporal Databases, SSTD 2013, held in Munich, Germany, in August 2013. The 24 revised full papers presented were carefully reviewed and selected from 58 submissions. The papers are organized in topical sections on joins and algorithms; mining and discovery; indexing; trajectories and road network data; nearest neighbours queries; uncertainty; and demonstrations.

Applied Mixed Models In Medicine

Author: Helen Brown
Publisher: John Wiley & Sons
ISBN: 1118778243
Size: 64.95 MB
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A fully updated edition of this key text on mixed models, focusing on applications in medical research The application of mixed models is an increasingly popular way of analysing medical data, particularly in the pharmaceutical industry. A mixed model allows the incorporation of both fixed and random variables within a statistical analysis, enabling efficient inferences and more information to be gained from the data. There have been many recent advances in mixed modelling, particularly regarding the software and applications. This third edition of Brown and Prescott’s groundbreaking text provides an update on the latest developments, and includes guidance on the use of current SAS techniques across a wide range of applications. Presents an overview of the theory and applications of mixed models in medical research, including the latest developments and new sections on incomplete block designs and the analysis of bilateral data. Easily accessible to practitioners in any area where mixed models are used, including medical statisticians and economists. Includes numerous examples using real data from medical and health research, and epidemiology, illustrated with SAS code and output. Features the new version of SAS, including new graphics for model diagnostics and the procedure PROC MCMC. Supported by a website featuring computer code, data sets, and further material. This third edition will appeal to applied statisticians working in medical research and the pharmaceutical industry, as well as teachers and students of statistics courses in mixed models. The book will also be of great value to a broad range of scientists, particularly those working in the medical and pharmaceutical areas.

Crossover Designs

Author: Kung-Jong Lui
Publisher: John Wiley & Sons
ISBN: 1119114691
Size: 57.96 MB
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A comprehensive and practical resource for analyses of crossover designs For ethical reasons, it is vital to keep the number of patients in a clinical trial as low as possible. As evidenced by extensive research publications, crossover design can be a useful and powerful tool to reduce the number of patients needed for a parallel group design in studying treatments for non-curable chronic diseases. This book introduces commonly-used and well-established statistical tests and estimators in epidemiology that can easily be applied to hypothesis testing and estimation of the relative treatment effect for various types of data scale in crossover designs. Models with distribution-free random effects are assumed and hence most approaches considered here are semi-parametric. The book provides clinicians and biostatisticians with the exact test procedures and exact interval estimators, which are applicable even when the number of patients in a crossover trial is small. Systematic discussion on sample size determination is also included, which will be a valuable resource for researchers involved in crossover trial design. Key features: Provides exact test procedures and interval estimators, which are especially of use in small-sample cases. Presents most test procedures and interval estimators in closed-forms, enabling readers to calculate them by use of a pocket calculator or commonly-used statistical packages. Each chapter is self-contained, allowing the book to be used a reference resource. Uses real-life examples to illustrate the practical use of test procedures and estimators Provides extensive exercises to help readers appreciate the underlying theory, learn other relevant test procedures and understand how to calculate the required sample size. Crossover Designs: Testing, Estimation and Sample Size will be a useful resource for researchers from biostatistics, as well as pharmaceutical and clinical sciences. It can also be used as a textbook or reference for graduate students studying clinical experiments.

Spatial Data Analysis

Author: Robert P. Haining
Publisher: Cambridge University Press
ISBN: 9780521774376
Size: 61.54 MB
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This book, first published in 2003, is a comprehensive overview of the theory and practice of spatial data analysis for students and researchers.

Statistical Methods For Evaluating Safety In Medical Product Development

Author: A. Lawrence Gould
Publisher: John Wiley & Sons
ISBN: 1118763106
Size: 19.40 MB
Format: PDF, Docs
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This book gives professionals in clinical research valuable information on the challenging issues of the design, execution, and management of clinical trials, and how to resolve these issues effectively. It also provides understanding and practical guidance on the application of contemporary statistical methods to contemporary issues in safety evaluation during medical product development. Each chapter provides sufficient detail to the reader to undertake the design and analysis of experiments at various stages of product development, including comprehensive references to the relevant literature. Provides a guide to statistical methods and application in medical product development Assists readers in undertaking design and analysis of experiments at various stages of product development Features case studies throughout the book, as well as, SAS and R code

Spatial Statistics And Geostatistics

Author: Yongwan Chun
Publisher: SAGE
ISBN: 1446291626
Size: 66.56 MB
Format: PDF, ePub, Docs
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"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.

Spatio Temporal Design

Author: Jorge Mateu
Publisher: John Wiley & Sons
ISBN: 1118441885
Size: 21.68 MB
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A state-of-the-art presentation of optimum spatio-temporal sampling design - bridging classic ideas with modern statistical modeling concepts and the latest computational methods. Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem at hand. Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to discuss optimum spatio-temporal sampling design. Spatio-temporal Design: Advances in Efficient Data Acquisition: Provides an up-to-date account of how to collect space-time data for monitoring, with a focus on statistical aspects and the latest computational methods Discusses basic methods and distinguishes between design and model-based approaches to collecting space-time data. Features model-based frequentist design for univariate and multivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout the book in order to demonstrate the different approaches and their integration. Includes real data sets, data generating mechanisms and simulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book for graduate level students as well as a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Statistical Analysis And Modelling Of Spatial Point Patterns

Author: Dr. Janine Illian
Publisher: John Wiley & Sons
ISBN: 9780470725153
Size: 34.77 MB
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Spatial point processes are mathematical models used to describe and analyse the geometrical structure of patterns formed by objects that are irregularly or randomly distributed in one-, two- or three-dimensional space. Examples include locations of trees in a forest, blood particles on a glass plate, galaxies in the universe, and particle centres in samples of material. Numerous aspects of the nature of a specific spatial point pattern may be described using the appropriate statistical methods. Statistical Analysis and Modelling of Spatial Point Patterns provides a practical guide to the use of these specialised methods. The application-oriented approach helps demonstrate the benefits of this increasingly popular branch of statistics to a broad audience. The book: Provides an introduction to spatial point patterns for researchers across numerous areas of application Adopts an extremely accessible style, allowing the non-statistician complete understanding Describes the process of extracting knowledge from the data, emphasising the marked point process Demonstrates the analysis of complex datasets, using applied examples from areas including biology, forestry, and materials science Features a supplementary website containing example datasets. Statistical Analysis and Modelling of Spatial Point Patterns is ideally suited for researchers in the many areas of application, including environmental statistics, ecology, physics, materials science, geostatistics, and biology. It is also suitable for students of statistics, mathematics, computer science, biology and geoinformatics.

Simplicity Complexity And Modelling

Author: Mike Christie
Publisher: John Wiley & Sons
ISBN: 1119960967
Size: 41.68 MB
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Several points of disagreement exist between different modelling traditions as to whether complex models are always better than simpler models, as to how to combine results from different models and how to propagate model uncertainty into forecasts. This book represents the result of collaboration between scientists from many disciplines to show how these conflicts can be resolved. Key Features: Introduces important concepts in modelling, outlining different traditions in the use of simple and complex modelling in statistics. Provides numerous case studies on complex modelling, such as climate change, flood risk and new drug development. Concentrates on varying models, including flood risk analysis models, the petrol industry forecasts and summarizes the evolution of water distribution systems. Written by experienced statisticians and engineers in order to facilitate communication between modellers in different disciplines. Provides a glossary giving terms commonly used in different modelling traditions. This book provides a much-needed reference guide to approaching statistical modelling. Scientists involved with modelling complex systems in areas such as climate change, flood prediction and prevention, financial market modelling and systems engineering will benefit from this book. It will also be a useful source of modelling case histories.