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After more than 15 years of development drawing on research in cognitive psychology, statistical graphics, computer science, and cartography, micromap designs are becoming part of mainstream statistical visualizations. Bringing together the research of two leaders in this field, Visualizing Data Patterns with Micromaps presents the many design vari
Book Synopsis Visualizing Data Patterns with Micromaps by : Daniel B. Carr
Download or read book Visualizing Data Patterns with Micromaps written by Daniel B. Carr and published by CRC Press. This book was released on 2010-04-29 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: After more than 15 years of development drawing on research in cognitive psychology, statistical graphics, computer science, and cartography, micromap designs are becoming part of mainstream statistical visualizations. Bringing together the research of two leaders in this field, Visualizing Data Patterns with Micromaps presents the many design vari
This dissertation addresses the visualization of spatio-temporal data for the purposes of communication, understanding, discovery, and analysis. A common approach to spatio-temporal visualization seeks to convey changes by showing a sequence of maps over time that does not address the problem of change blindness. The dissertation builds upon and extends the work of Carr and Pickle [2010] that calls attention to this problem and addresses visualization of spatial data patterns with conditioned and comparative micromaps The dissertation adds dynamic interactivity to the comparative maps that address change blindness, develops new designs and demonstrates their use. Examples use the resulting interactive visualization tool named TCmaps (Temporal Change maps) to illustrate the designs and general utility by showing data from a variety of domains including health, education, environment, demography, and ecology. The examples show that one can see, point at and talk about all the changes designated by interactive thresholds since the changes are shown explicitly in separate maps sequences. The interactive designs address additional issues such as setting thresholds for categories whose changes are to be observed and methods for viewing change map sequences that are too long to see in one view. TCmaps is a general visual analytical tool. The dissertation emphasizes displaying results for two kinds of simulation models. One is a computational fluid dynamics model that simulates the transport and dispersion of toxic releases. The second shows the application of TCmaps to understanding the spread of an invasive species, the Eurasian Collared-Dove (ECD) in the United States. In the last two decades researchers have developed many spatio-temporal models to characterize the invasion of ECD. This research modifies the hierarchical Bayesian matrix model developed by Hooten et al. [2006a] to provide new simulation results that better account for the species' mysterious northwestern expansion. In this case study, TCmaps provides a powerful platform to display the spatial context of bird survey routes, observations, estimates, forecasts and variances. Since the research and methodology development in this dissertation builds on advances in the cognitive, data, statistics, and computing sciences, the results are of potential interest for a large domain of application.
Book Synopsis Interfaces and Visual Analytics for Visualizing Spatio-temporal Data with Micromaps by : Chunling Zhang
Download or read book Interfaces and Visual Analytics for Visualizing Spatio-temporal Data with Micromaps written by Chunling Zhang and published by . This book was released on 2012 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation addresses the visualization of spatio-temporal data for the purposes of communication, understanding, discovery, and analysis. A common approach to spatio-temporal visualization seeks to convey changes by showing a sequence of maps over time that does not address the problem of change blindness. The dissertation builds upon and extends the work of Carr and Pickle [2010] that calls attention to this problem and addresses visualization of spatial data patterns with conditioned and comparative micromaps The dissertation adds dynamic interactivity to the comparative maps that address change blindness, develops new designs and demonstrates their use. Examples use the resulting interactive visualization tool named TCmaps (Temporal Change maps) to illustrate the designs and general utility by showing data from a variety of domains including health, education, environment, demography, and ecology. The examples show that one can see, point at and talk about all the changes designated by interactive thresholds since the changes are shown explicitly in separate maps sequences. The interactive designs address additional issues such as setting thresholds for categories whose changes are to be observed and methods for viewing change map sequences that are too long to see in one view. TCmaps is a general visual analytical tool. The dissertation emphasizes displaying results for two kinds of simulation models. One is a computational fluid dynamics model that simulates the transport and dispersion of toxic releases. The second shows the application of TCmaps to understanding the spread of an invasive species, the Eurasian Collared-Dove (ECD) in the United States. In the last two decades researchers have developed many spatio-temporal models to characterize the invasion of ECD. This research modifies the hierarchical Bayesian matrix model developed by Hooten et al. [2006a] to provide new simulation results that better account for the species' mysterious northwestern expansion. In this case study, TCmaps provides a powerful platform to display the spatial context of bird survey routes, observations, estimates, forecasts and variances. Since the research and methodology development in this dissertation builds on advances in the cognitive, data, statistics, and computing sciences, the results are of potential interest for a large domain of application.
The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
Book Synopsis New Developments in Statistical Modeling, Inference and Application by : Zhezhen Jin
Download or read book New Developments in Statistical Modeling, Inference and Application written by Zhezhen Jin and published by Springer. This book was released on 2016-10-28 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this volume represent the most timely and advanced contributions to the 2014 Joint Applied Statistics Symposium of the International Chinese Statistical Association (ICSA) and the Korean International Statistical Society (KISS), held in Portland, Oregon. The contributions cover new developments in statistical modeling and clinical research: including model development, model checking, and innovative clinical trial design and analysis. Each paper was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and government agencies around the world, including from North America, Asia, and Europe. It offered 3 keynote speeches, 7 short courses, 76 parallel scientific sessions, student paper sessions, and social events.
This comprehensive and well-established cartography textbook covers the theory and the practical applications of map design and the appropriate use of map elements. It explains the basic methods for visualizing and analyzing spatial data and introduces the latest cutting-edge data visualization techniques. The fourth edition responds to the extensive developments in cartography and GIS in the last decade, including the continued evolution of the Internet and Web 2.0; the need to analyze and visualize large data sets (commonly referred to as Big Data); the changes in computer hardware (e.g., the evolution of hardware for virtual environments and augmented reality); and novel applications of technology. Key Features of the Fourth Edition: Includes more than 400 color illustrations and it is available in both print and eBook formats. A new chapter on Geovisual Analytics and individual chapters have now been dedicated to Map Elements, Typography, Proportional Symbol Mapping, Dot Mapping, Cartograms, and Flow Mapping. Extensive revisions have been made to the chapters on Principles of Color, Dasymetric Mapping, Visualizing Terrain, Map Animation, Visualizing Uncertainty, and Virtual Environments/Augmented Reality. All chapters include Learning Objectives and Study Questions. Provides more than 250 web links to online content, over 730 references to scholarly materials, and additional 540 references available for Further Reading. There is ample material for either a one or two-semester course in thematic cartography and geovisualization. This textbook provides undergraduate and graduate students in geoscience, geography, and environmental sciences with the most valuable up-to-date learning resource available in the cartographic field. It is a great resource for professionals and experts using GIS and Cartography and for organizations and policy makers involved in mapping projects.
Book Synopsis Thematic Cartography and Geovisualization, Fourth Edition by : Terry A. Slocum
Download or read book Thematic Cartography and Geovisualization, Fourth Edition written by Terry A. Slocum and published by CRC Press. This book was released on 2022-08-18 with total page 1383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive and well-established cartography textbook covers the theory and the practical applications of map design and the appropriate use of map elements. It explains the basic methods for visualizing and analyzing spatial data and introduces the latest cutting-edge data visualization techniques. The fourth edition responds to the extensive developments in cartography and GIS in the last decade, including the continued evolution of the Internet and Web 2.0; the need to analyze and visualize large data sets (commonly referred to as Big Data); the changes in computer hardware (e.g., the evolution of hardware for virtual environments and augmented reality); and novel applications of technology. Key Features of the Fourth Edition: Includes more than 400 color illustrations and it is available in both print and eBook formats. A new chapter on Geovisual Analytics and individual chapters have now been dedicated to Map Elements, Typography, Proportional Symbol Mapping, Dot Mapping, Cartograms, and Flow Mapping. Extensive revisions have been made to the chapters on Principles of Color, Dasymetric Mapping, Visualizing Terrain, Map Animation, Visualizing Uncertainty, and Virtual Environments/Augmented Reality. All chapters include Learning Objectives and Study Questions. Provides more than 250 web links to online content, over 730 references to scholarly materials, and additional 540 references available for Further Reading. There is ample material for either a one or two-semester course in thematic cartography and geovisualization. This textbook provides undergraduate and graduate students in geoscience, geography, and environmental sciences with the most valuable up-to-date learning resource available in the cartographic field. It is a great resource for professionals and experts using GIS and Cartography and for organizations and policy makers involved in mapping projects.
Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
Book Synopsis Exploratory Data Analysis with MATLAB by : Wendy L. Martinez
Download or read book Exploratory Data Analysis with MATLAB written by Wendy L. Martinez and published by CRC Press. This book was released on 2017-08-07 with total page 589 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition: "The authors present an intuitive and easy-to-read book. ... accompanied by many examples, proposed exercises, good references, and comprehensive appendices that initiate the reader unfamiliar with MATLAB." —Adolfo Alvarez Pinto, International Statistical Review "Practitioners of EDA who use MATLAB will want a copy of this book. ... The authors have done a great service by bringing together so many EDA routines, but their main accomplishment in this dynamic text is providing the understanding and tools to do EDA. —David A Huckaby, MAA Reviews Exploratory Data Analysis (EDA) is an important part of the data analysis process. The methods presented in this text are ones that should be in the toolkit of every data scientist. As computational sophistication has increased and data sets have grown in size and complexity, EDA has become an even more important process for visualizing and summarizing data before making assumptions to generate hypotheses and models. Exploratory Data Analysis with MATLAB, Third Edition presents EDA methods from a computational perspective and uses numerous examples and applications to show how the methods are used in practice. The authors use MATLAB code, pseudo-code, and algorithm descriptions to illustrate the concepts. The MATLAB code for examples, data sets, and the EDA Toolbox are available for download on the book’s website. New to the Third Edition Random projections and estimating local intrinsic dimensionality Deep learning autoencoders and stochastic neighbor embedding Minimum spanning tree and additional cluster validity indices Kernel density estimation Plots for visualizing data distributions, such as beanplots and violin plots A chapter on visualizing categorical data
Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field. Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions. Features Provides the first book and a single source of information on RWE in drug development Covers a broad array of topics on outcomes- and value-based RWE assessments Demonstrates proper Bayesian application and causal inference for real-world data (RWD) Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise
Book Synopsis Real-World Evidence in Drug Development and Evaluation by : Harry Yang
Download or read book Real-World Evidence in Drug Development and Evaluation written by Harry Yang and published by CRC Press. This book was released on 2021-01-11 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: Real-world evidence (RWE) has been at the forefront of pharmaceutical innovations. It plays an important role in transforming drug development from a process aimed at meeting regulatory expectations to an operating model that leverages data from disparate sources to aid business, regulatory, and healthcare decision making. Despite its many benefits, there is no single book systematically covering the latest development in the field. Written specifically for pharmaceutical practitioners, Real-World Evidence in Drug Development and Evaluation, presents a wide range of RWE applications throughout the lifecycle of drug product development. With contributions from experienced researchers in the pharmaceutical industry, the book discusses at length RWE opportunities, challenges, and solutions. Features Provides the first book and a single source of information on RWE in drug development Covers a broad array of topics on outcomes- and value-based RWE assessments Demonstrates proper Bayesian application and causal inference for real-world data (RWD) Presents real-world use cases to illustrate the use of advanced analytics and statistical methods to generate insights Offers a balanced discussion of practical RWE issues at hand and technical solutions suitable for practitioners with limited data science expertise
This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed, but no previous knowledge of GIS or mapping is required. Key Features: • Includes spatial perspectives on cluster analysis • Focuses on exploring spatial data • Supplemented by extensive support with sample data sets and examples on the GeoDaCenter website This book is both useful as a reference for the software and as a text for students and researchers of spatial data science. Luc Anselin is the Founding Director of the Center for Spatial Data Science at the University of Chicago, where he is also the Stein-Freiler Distinguished Service Professor of Sociology and the College, as well as a member of the Committee on Data Science. He is the creator of the GeoDa software and an active contributor to the PySAL Python open-source software library for spatial analysis. He has written widely on topics dealing with the methodology of spatial data analysis, including his classic 1988 text on Spatial Econometrics. His work has been recognized by many awards, such as his election to the U.S. National Academy of Science and the American Academy of Arts and Science.
Book Synopsis An Introduction to Spatial Data Science with GeoDa by : Luc Anselin
Download or read book An Introduction to Spatial Data Science with GeoDa written by Luc Anselin and published by CRC Press. This book was released on 2024-04-26 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the first in a two-volume series that introduces the field of spatial data science. It offers an accessible overview of the methodology of exploratory spatial data analysis. It also constitutes the definitive user’s guide for the widely adopted GeoDa open-source software for spatial analysis. Leveraging a large number of real-world empirical illustrations, readers will gain an understanding of the main concepts and techniques, using dynamic graphics for thematic mapping, statistical graphing, and, most centrally, the analysis of spatial autocorrelation. Key to this analysis is the concept of local indicators of spatial association, pioneered by the author and recently extended to the analysis of multivariate data. The focus of the book is on intuitive methods to discover interesting patterns in spatial data. It offers a progression from basic data manipulation through description and exploration to the identification of clusters and outliers by means of local spatial autocorrelation analysis. A distinctive approach is to spatialize intrinsically non-spatial methods by means of linking and brushing with a range of map representations, including several that are unique to the GeoDa software. The book also represents the most in-depth treatment of local spatial autocorrelation and its visualization and interpretation by means of GeoDa. The book is intended for readers interested in going beyond simple mapping of geographical data to gain insight into interesting patterns. Some basic familiarity with statistical concepts is assumed, but no previous knowledge of GIS or mapping is required. Key Features: • Includes spatial perspectives on cluster analysis • Focuses on exploring spatial data • Supplemented by extensive support with sample data sets and examples on the GeoDaCenter website This book is both useful as a reference for the software and as a text for students and researchers of spatial data science. Luc Anselin is the Founding Director of the Center for Spatial Data Science at the University of Chicago, where he is also the Stein-Freiler Distinguished Service Professor of Sociology and the College, as well as a member of the Committee on Data Science. He is the creator of the GeoDa software and an active contributor to the PySAL Python open-source software library for spatial analysis. He has written widely on topics dealing with the methodology of spatial data analysis, including his classic 1988 text on Spatial Econometrics. His work has been recognized by many awards, such as his election to the U.S. National Academy of Science and the American Academy of Arts and Science.
The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.
Book Synopsis Handbook of Computational Statistics by : James E. Gentle
Download or read book Handbook of Computational Statistics written by James E. Gentle and published by Springer Science & Business Media. This book was released on 2012-07-06 with total page 1180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Handbook of Computational Statistics - Concepts and Methods (second edition) is a revision of the first edition published in 2004, and contains additional comments and updated information on the existing chapters, as well as three new chapters addressing recent work in the field of computational statistics. This new edition is divided into 4 parts in the same way as the first edition. It begins with "How Computational Statistics became the backbone of modern data science" (Ch.1): an overview of the field of Computational Statistics, how it emerged as a separate discipline, and how its own development mirrored that of hardware and software, including a discussion of current active research. The second part (Chs. 2 - 15) presents several topics in the supporting field of statistical computing. Emphasis is placed on the need for fast and accurate numerical algorithms, and some of the basic methodologies for transformation, database handling, high-dimensional data and graphics treatment are discussed. The third part (Chs. 16 - 33) focuses on statistical methodology. Special attention is given to smoothing, iterative procedures, simulation and visualization of multivariate data. Lastly, a set of selected applications (Chs. 34 - 38) like Bioinformatics, Medical Imaging, Finance, Econometrics and Network Intrusion Detection highlight the usefulness of computational statistics in real-world applications.
National Patterns of R&D Resources is an annual report issued by the National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation, which provides a national view of current 'patterns' in funding of R&D activities in government, industry, academia, federally funded research and development centers, and non-profits. Total R&D funds are broken out at the national level by type of provider, type of recipient, and whether the R&D is basic, applied, or developmental. These patterns are compared both longitudinally versus historical R&D amounts, and internationally. This report series, which is based on input from several censuses and surveys, is used to formulate policies that, e.g., might increase incentives to support different types, sources, or recipients of R&D than is currently the case. To communicate these R&D patterns, each report is composed of a set of tabulations of national R&D disaggregated by type of donor, type of recipient, and type of R&D. While this satisfies many key user groups, the question was whether some modifications of the report could attract a wider user community and at the same time provide more useful information for current users. National Patterns of R&D Resources: Future Directions for Content and Methods addresses the following questions: (1) what additional topics and tabulations could be presented without modifying the current portfolio of R&D censuses and surveys, (2) what additional topics and tabulations might be presented by expanding these current data collections, (3) what could be done to enhance international comparability of the tabulations, (4) since much of the information on non-profit R&D providers and recipients is estimated from 15 year-old data, what impact might this be having on the quality of the associated National Patterns tabulations, (5) what statistical models could be used to support the issuance R&D estimates at state-level and geographic regions below the national level, (6) what use could be made from the recent development of administrative sources of R&D information, and finally, (7) what graphical tools could be added to the current tabulations to enhance the communication of R&D patterns to the users of this series of publications.
Book Synopsis National Patterns of R&D Resources by : National Research Council
Download or read book National Patterns of R&D Resources written by National Research Council and published by National Academies Press. This book was released on 2013-08-09 with total page 121 pages. Available in PDF, EPUB and Kindle. Book excerpt: National Patterns of R&D Resources is an annual report issued by the National Center for Science and Engineering Statistics (NCSES) of the National Science Foundation, which provides a national view of current 'patterns' in funding of R&D activities in government, industry, academia, federally funded research and development centers, and non-profits. Total R&D funds are broken out at the national level by type of provider, type of recipient, and whether the R&D is basic, applied, or developmental. These patterns are compared both longitudinally versus historical R&D amounts, and internationally. This report series, which is based on input from several censuses and surveys, is used to formulate policies that, e.g., might increase incentives to support different types, sources, or recipients of R&D than is currently the case. To communicate these R&D patterns, each report is composed of a set of tabulations of national R&D disaggregated by type of donor, type of recipient, and type of R&D. While this satisfies many key user groups, the question was whether some modifications of the report could attract a wider user community and at the same time provide more useful information for current users. National Patterns of R&D Resources: Future Directions for Content and Methods addresses the following questions: (1) what additional topics and tabulations could be presented without modifying the current portfolio of R&D censuses and surveys, (2) what additional topics and tabulations might be presented by expanding these current data collections, (3) what could be done to enhance international comparability of the tabulations, (4) since much of the information on non-profit R&D providers and recipients is estimated from 15 year-old data, what impact might this be having on the quality of the associated National Patterns tabulations, (5) what statistical models could be used to support the issuance R&D estimates at state-level and geographic regions below the national level, (6) what use could be made from the recent development of administrative sources of R&D information, and finally, (7) what graphical tools could be added to the current tabulations to enhance the communication of R&D patterns to the users of this series of publications.
Modern Statistical Methodology and Software for Analyzing Spatial Point PatternsSpatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on th
Book Synopsis Spatial Point Patterns by : Adrian Baddeley
Download or read book Spatial Point Patterns written by Adrian Baddeley and published by CRC Press. This book was released on 2015-11-11 with total page 830 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern Statistical Methodology and Software for Analyzing Spatial Point PatternsSpatial Point Patterns: Methodology and Applications with R shows scientific researchers and applied statisticians from a wide range of fields how to analyze their spatial point pattern data. Making the techniques accessible to non-mathematicians, the authors draw on th