Statistical Analysis Of Spatial And Spatio Temporal Point Patterns Third Edition

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Statistical Analysis Of Spatial And Spatio Temporal Point Patterns
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Author : Peter J. Diggle
language : en
Publisher: CRC Press
Release Date : 2013-07-23
Statistical Analysis Of Spatial And Spatio Temporal Point Patterns written by Peter J. Diggle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-23 with Mathematics categories.
Retaining all the material from the second edition and adding substantial new material, this third edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this edition now covers spatio-temporal point patterns. It also incorporates the use of R through several packages dedicated to the analysis of spatial point process data, with code and data sets available online. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences.
Statistical Analysis Of Spatial And Spatio Temporal Point Patterns Third Edition
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Author : Peter J. Diggle
language : en
Publisher: CRC Press
Release Date : 2013-07-23
Statistical Analysis Of Spatial And Spatio Temporal Point Patterns Third Edition written by Peter J. Diggle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-07-23 with Mathematics categories.
Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author’s website.
Handbook Of Infectious Disease Data Analysis
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Author : Leonhard Held
language : en
Publisher: CRC Press
Release Date : 2019-11-07
Handbook Of Infectious Disease Data Analysis written by Leonhard Held and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-07 with Medical categories.
Recent years have seen an explosion in new kinds of data on infectious diseases, including data on social contacts, whole genome sequences of pathogens, biomarkers for susceptibility to infection, serological panel data, and surveillance data. The Handbook of Infectious Disease Data Analysis provides an overview of many key statistical methods that have been developed in response to such new data streams and the associated ability to address key scientific and epidemiological questions. A unique feature of the Handbook is the wide range of topics covered. Key features Contributors include many leading researchers in the field Divided into four main sections: Basic concepts, Analysis of Outbreak Data, Analysis of Seroprevalence Data, Analysis of Surveillance Data Numerous case studies and examples throughout Provides both introductory material and key reference material
Spatial Point Patterns
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Author : Adrian Baddeley
language : en
Publisher: CRC Press
Release Date : 2015-11-11
Spatial Point Patterns written by Adrian Baddeley and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-11-11 with Mathematics categories.
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
Design And Analysis Of Cross Over Trials Third Edition
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Author : Byron Jones
language : en
Publisher: CRC Press
Release Date : 2014-10-08
Design And Analysis Of Cross Over Trials Third Edition written by Byron Jones and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-08 with Mathematics categories.
Design and Analysis of Cross-Over Trials is concerned with a specific kind of comparative trial known as the cross-over trial, in which subjects receive different sequences of treatments. Such trials are widely used in clinical and medical research, and in other diverse areas such as veterinary science, psychology, sports science, and agriculture. The first edition of this book was the first to be wholly devoted to the subject. The second edition was revised to mirror growth and development in areas where the design remained in widespread use and new areas where it had grown in importance. This new Third Edition: Contains seven new chapters written in the form of short case studies that address re-estimating sample size when testing for average bioequivalence, fitting a nonlinear dose response function, estimating a dose to take forward from phase two to phase three, establishing proof of concept, and recalculating the sample size using conditional power Employs the R package Crossover, specially created to accompany the book and provide a graphical user interface for locating designs in a large catalog and for searching for new designs Includes updates regarding the use of period baselines and the analysis of data from very small trials Reflects the availability of new procedures in SAS, particularly proc glimmix Presents the SAS procedure proc mcmc as an alternative to WinBUGS for Bayesian analysis Complete with real data and downloadable SAS code, Design and Analysis of Cross-Over Trials, Third Edition provides a practical understanding of the latest methods along with the necessary tools for implementation.
State Space Methods For Time Series Analysis
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Author : Jose Casals
language : en
Publisher: CRC Press
Release Date : 2018-09-03
State Space Methods For Time Series Analysis written by Jose Casals and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-03 with Mathematics categories.
The state-space approach provides a formal framework where any result or procedure developed for a basic model can be seamlessly applied to a standard formulation written in state-space form. Moreover, it can accommodate with a reasonable effort nonstandard situations, such as observation errors, aggregation constraints, or missing in-sample values. Exploring the advantages of this approach, State-Space Methods for Time Series Analysis: Theory, Applications and Software presents many computational procedures that can be applied to a previously specified linear model in state-space form. After discussing the formulation of the state-space model, the book illustrates the flexibility of the state-space representation and covers the main state estimation algorithms: filtering and smoothing. It then shows how to compute the Gaussian likelihood for unknown coefficients in the state-space matrices of a given model before introducing subspace methods and their application. It also discusses signal extraction, describes two algorithms to obtain the VARMAX matrices corresponding to any linear state-space model, and addresses several issues relating to the aggregation and disaggregation of time series. The book concludes with a cross-sectional extension to the classical state-space formulation in order to accommodate longitudinal or panel data. Missing data is a common occurrence here, and the book explains imputation procedures necessary to treat missingness in both exogenous and endogenous variables. Web Resource The authors’ E4 MATLAB® toolbox offers all the computational procedures, administrative and analytical functions, and related materials for time series analysis. This flexible, powerful, and free software tool enables readers to replicate the practical examples in the text and apply the procedures to their own work.
Introduction To High Dimensional Statistics
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Author : Christophe Giraud
language : en
Publisher: CRC Press
Release Date : 2014-12-17
Introduction To High Dimensional Statistics written by Christophe Giraud and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-12-17 with Business & Economics categories.
Ever-greater computing technologies have given rise to an exponentially growing volume of data. Today massive data sets (with potentially thousands of variables) play an important role in almost every branch of modern human activity, including networks, finance, and genetics. However, analyzing such data has presented a challenge for statisticians
Spatial Analysis Using Big Data
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Author : Yoshiki Yamagata
language : en
Publisher: Academic Press
Release Date : 2019-11-03
Spatial Analysis Using Big Data written by Yoshiki Yamagata and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-03 with Business & Economics categories.
Spatial Analysis Using Big Data: Methods and Urban Applications helps readers understand the most powerful, state-of-the-art spatial econometric methods, focusing particularly on urban research problems. The methods represent a cluster of potentially transformational socio-economic modeling tools that allow researchers to capture real-time and high-resolution information to potentially reveal new socioeconomic dynamics within urban populations. Each method, written by leading exponents of the discipline, uses real-time urban big data to solve research problems in spatial science. Urban applications of these methods are provided in unsurpassed depth, with chapters on surface temperature mapping, view value analysis, community clustering and spatial-social networks, among many others. - Reviews some of the most powerful and challenging modern methods to study big data problems in spatial science - Provides computer codes written in R, MATLAB and Python to help implement methods - Applies these methods to common problems observed in urban and regional economics
Statistical Learning With Sparsity
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Author : Trevor Hastie
language : en
Publisher: CRC Press
Release Date : 2015-05-07
Statistical Learning With Sparsity written by Trevor Hastie and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-05-07 with Business & Economics categories.
Discover New Methods for Dealing with High-Dimensional DataA sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underl
Measuring Statistical Evidence Using Relative Belief
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Author : Michael Evans
language : en
Publisher: CRC Press
Release Date : 2015-06-23
Measuring Statistical Evidence Using Relative Belief written by Michael Evans and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-23 with Mathematics categories.
This book provides an overview of recent work on developing a theory of statistical inference based on measuring statistical evidence. It attempts to establish a gold standard for how a statistical analysis should proceed. The book illustrates relative belief theory using many examples and describes the strengths and weaknesses of the theory. The author also addresses fundamental statistical issues, including the meaning of probability, the role of subjectivity, the meaning of objectivity, and the role of infinity and continuity.