Modern Directional Statistics

Author: Christophe Ley,Thomas Verdebout

Publisher: CRC Press

ISBN: 1351645781

Category: Computers

Page: 176

View: 2485


Modern Directional Statistics collects important advances in methodology and theory for directional statistics over the last two decades. It provides a detailed overview and analysis of recent results that can help both researchers and practitioners. Knowledge of multivariate statistics eases the reading but is not mandatory. The field of directional statistics has received a lot of attention over the past two decades, due to new demands from domains such as life sciences or machine learning, to the availability of massive data sets requiring adapted statistical techniques, and to technological advances. This book covers important progresses in distribution theory,high-dimensional statistics, kernel density estimation, efficient inference on directional supports, and computational and graphical methods. Christophe Ley is professor of mathematical statistics at Ghent University. His research interests include semi-parametrically efficient inference, flexible modeling, directional statistics and the study of asymptotic approximations via Stein’s Method. His achievements include the Marie-Jeanne Laurent-Duhamel prize of the Société Française de Statistique and an elected membership at the International Statistical Institute. He is associate editor for the journals Computational Statistics & Data Analysis and Econometrics and Statistics. Thomas Verdebout is professor of mathematical statistics at Université libre de Bruxelles (ULB). His main research interests are semi-parametric statistics, high- dimensional statistics, directional statistics and rank-based procedures. He has won an annual prize of the Belgian Academy of Sciences and is an elected member of the International Statistical Institute. He is associate editor for the journals Statistics and Probability Letters and Journal of Multivariate Analysis.

Directional Statistics

Author: Kanti V. Mardia,Peter E. Jupp

Publisher: John Wiley & Sons

ISBN: 0470317817

Category: Mathematics

Page: 460

View: 4420


Presents new and up-dated material on both the underlying theory and the practical methodology of directional statistics, helping the reader to utilise and develop the techniques appropriate to their work. The book is divided into three parts. The first part concentrates on statistics on the circle. Topics covered include tests of uniformity, tests of good-of-fit, inference on von Mises distributions and non-parametric methods. The second part considers statistics on spheres of arbitrary dimension, and includes a detailed account of inference on the main distributions on spheres. Recent material on correlation, regression time series, robust techniques, bootstrap methods, density estimation and curve fitting is presented. The third part considers statistics on more general sample spaces, in particular rotation groups, Stiefel manifolds, Grassmann manifolds and complex projective spaces. Shape analysis is considered from the perspective of directional statistics. Written by leading authors in the field, this text will be invaluable not only to researchers in probability and statistics interested in the latest developments in directional statistics, but also to practitioners and researchers in many scientific fields, including astronomy, biology, computer vision, earth sciences and image analysis.

Circular Statistics in R

Author: Arthur Pewsey,Markus Neuhäuser,Graeme D Ruxton

Publisher: OUP Oxford

ISBN: 0191650765

Category: Mathematics

Page: 192

View: 4730


Circular Statistics in R provides the most comprehensive guide to the analysis of circular data in over a decade. Circular data arise in many scientific contexts whether it be angular directions such as: observed compass directions of departure of radio-collared migratory birds from a release point; bond angles measured in different molecules; wind directions at different times of year at a wind farm; direction of stress-fractures in concrete bridge supports; longitudes of earthquake epicentres or seasonal and daily activity patterns, for example: data on the times of day at which animals are caught in a camera trap, or in 911 calls in New York, or in internet traffic; variation throughout the year in measles incidence, global energy requirements, TV viewing figures or injuries to athletes. The natural way of representing such data graphically is as points located around the circumference of a circle, hence their name. Importantly, circular variables are periodic in nature and the origin, or zero point, such as the beginning of a new year, is defined arbitrarily rather than necessarily emerging naturally from the system. This book will be of value both to those new to circular data analysis as well as those more familiar with the field. For beginners, the authors start by considering the fundamental graphical and numerical summaries used to represent circular data before introducing distributions that might be used to model them. They go on to discuss basic forms of inference such as point and interval estimation, as well as formal significance tests for hypotheses that will often be of scientific interest. When discussing model fitting, the authors advocate reduced reliance on the classical von Mises distribution; showcasing distributions that are capable of modelling features such as asymmetry and varying levels of kurtosis that are often exhibited by circular data. The use of likelihood-based and computer-intensive approaches to inference and modelling are stressed throughout the book. The R programming language is used to implement the methodology, particularly its "circular" package. Also provided are over 150 new functions for techniques not already covered within R. This concise but authoritative guide is accessible to the diverse range of scientists who have circular data to analyse and want to do so as easily and as effectively as possible.

Statistical Analysis of Circular Data

Author: N. I. Fisher

Publisher: Cambridge University Press

ISBN: 9780521568906

Category: Mathematics

Page: 277

View: 3172


This book provides a unified and up-to-date account of techniques for handling circular data, and will interest all who perform data analyses.

Bayesian Methods in Structural Bioinformatics

Author: Thomas Hamelryck,Kanti Mardia,Jesper Ferkinghoff-Borg

Publisher: Springer

ISBN: 3642272258

Category: Medical

Page: 386

View: 8851


This book is an edited volume, the goal of which is to provide an overview of the current state-of-the-art in statistical methods applied to problems in structural bioinformatics (and in particular protein structure prediction, simulation, experimental structure determination and analysis). It focuses on statistical methods that have a clear interpretation in the framework of statistical physics, rather than ad hoc, black box methods based on neural networks or support vector machines. In addition, the emphasis is on methods that deal with biomolecular structure in atomic detail. The book is highly accessible, and only assumes background knowledge on protein structure, with a minimum of mathematical knowledge. Therefore, the book includes introductory chapters that contain a solid introduction to key topics such as Bayesian statistics and concepts in machine learning and statistical physics.

Bayesian Disease Mapping

Hierarchical Modeling in Spatial Epidemiology, Third Edition

Author: Andrew B. Lawson

Publisher: CRC Press

ISBN: 1351271741

Category: Mathematics

Page: 464

View: 1725


Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the predictive modeling of health outcomes, and other spatial biostatistical areas. Exploring these new developments, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology, Third Edition provides an up-to-date, cohesive account of the full range of Bayesian disease mapping methods and applications. In addition to the new material, the book also covers more conventional areas such as relative risk estimation, clustering, spatial survival analysis, and longitudinal analysis. After an introduction to Bayesian inference, computation, and model assessment, the text focuses on important themes, including disease map reconstruction, cluster detection, regression and ecological analysis, putative hazard modeling, analysis of multiple scales and multiple diseases, spatial survival and longitudinal studies, spatiotemporal methods, and map surveillance. It shows how Bayesian disease mapping can yield significant insights into georeferenced health data. The target audience for this text is public health specialists, epidemiologists, and biostatisticians who need to work with geo-referenced health data.

Statistical Paradigms

Recent Advances and Reconciliations

Author: Ashis SenGupta,Tapas Samanta,Ayanendranath Basu

Publisher: World Scientific

ISBN: 9814644110

Category: Mathematics

Page: 308

View: 8554


This volume consists of a collection of research articles on classical and emerging Statistical Paradigms — parametric, non-parametric and semi-parametric, frequentist and Bayesian — encompassing both theoretical advances and emerging applications in a variety of scientific disciplines. For advances in theory, the topics include: Bayesian Inference, Directional Data Analysis, Distribution Theory, Econometrics and Multiple Testing Procedures. The areas in emerging applications include: Bioinformatics, Factorial Experiments and Linear Models, Hotspot Geoinformatics and Reliability. Contents:Reviews:Weak Paradoxes and Paradigms (Jayanta K Ghosh)Nonparametrics in Modern Interdisciplinary Research: Some Perspectives and Prospectives (Pranab K Sen)Parametric:Bounds on Distributions Involving Partial, Marginal and Conditional Information: The Consequences of Incomplete Prior Specification (Barry C Arnold)Stepdown Procedures Controlling a Generalized False Discovery Rate (Wenge Guo and Sanat K Sarkar)On Confidence Intervals for Expected Response in 2n Factorial Experiments with Exponentially Distributed Response Variables (H V Kulkarni and S C Patil)Predictive Influence of Variables in a Linear Regression Model when the Moment Matrix is Singular (Md Nurul Haque Mollah and S K Bhattacharjee)New Wrapped Distributions — Goodness of Fit (A V Dattatreya Rao, I Ramabhadra Sarma and S V S Girija)Semi-Parametric:Non-Stationary Samples and Meta-Distribution (Dominique Guégan)MDL Model Selection Criterion for Mixed Models with an Application to Spline Smoothing (Antti Liski and Erkki P Liski)Digital Governance and Hotspot Geoinformatics with Continuous Fractional Response (G P Patil, S W Joshi and R E Koli)Bayesian Curve Registration of Functional Data (Z Zhong, A Majumdar and R L Eubank)Non-Parametric & Probability:Nonparametric Estimation in a One-Way Error Component Model: A Monte Carlo Analysis (Daniel J Henderson and Aman Ullah)GERT Analysis of Consecutive-k Systems: An Overview (Kanwar Sen, Manju Agarwal and Pooja Mohan)Moment Bounds for Strong-Mixing Processes with Applications (Ratan Dasgupta) Readership: Researchers, professionals and advanced students working on Bayesian and frequentist approaches to statistical modeling and on interfaces for both theory and applications. Key Features:A scholarly and motivating review of non-parametric methods by P K Sen, winner of the Wilks Medal in 2010Discussion of paradoxes of the frequentist and Bayesian paradigms, related counterexamples, and their implicationsStands out in terms of the width and depthKeywords:Bayesian Inference;Design of Experiments;Econometrics;Hotspot Geoinformatics;Linear Models and Regression Analysis;Multiple Testing Procedures;Probability Distributions for Linear and Directional Data;Reliability

Applied Directional Statistics

Modern Methods and Case Studies

Author: Christophe Ley,Thomas Verdebout

Publisher: CRC Press

ISBN: 1351856529

Category: Mathematics

Page: 300

View: 4939


This book collects important advances in methodology and data analysis for directional statistics. It is the companion book of the more theoretical treatment presented in Modern Directional Statistics (CRC Press, 2017). The field of directional statistics has received a lot of attention due to demands from disciplines such as life sciences or machine learning, the availability of massive data sets requiring adapted statistical techniques, and technological advances. This book covers important progress in bioinformatics, biology, astrophysics, oceanography, environmental sciences, earth sciences, machine learning and social sciences.

Handbook of Statistical Systems Biology

Author: Michael Stumpf,David J. Balding,Mark Girolami

Publisher: John Wiley & Sons

ISBN: 1119952042

Category: Science

Page: 530

View: 7677


Systems Biology is now entering a mature phase in which the key issues are characterising uncertainty and stochastic effects in mathematical models of biological systems. The area is moving towards a full statistical analysis and probabilistic reasoning over the inferences that can be made from mathematical models. This handbook presents a comprehensive guide to the discipline for practitioners and educators, in providing a full and detailed treatment of these important and emerging subjects. Leading experts in systems biology and statistics have come together to provide insight in to the major ideas in the field, and in particular methods of specifying and fitting models, and estimating the unknown parameters. This book: Provides a comprehensive account of inference techniques in systems biology. Introduces classical and Bayesian statistical methods for complex systems. Explores networks and graphical modeling as well as a wide range of statistical models for dynamical systems. Discusses various applications for statistical systems biology, such as gene regulation and signal transduction. Features statistical data analysis on numerous technologies, including metabolic and transcriptomic technologies. Presents an in-depth presentation of reverse engineering approaches. Provides colour illustrations to explain key concepts. This handbook will be a key resource for researchers practising systems biology, and those requiring a comprehensive overview of this important field.

Mathematical Morphology in Geomorphology and GISci

Author: Behara Seshadri Daya Sagar

Publisher: CRC Press

ISBN: 1439872023

Category: Mathematics

Page: 546

View: 6792


Mathematical Morphology in Geomorphology and GISci presents a multitude of mathematical morphological approaches for processing and analyzing digital images in quantitative geomorphology and geographic information science (GISci). Covering many interdisciplinary applications, the book explains how to use mathematical morphology not only to perform quantitative morphologic and scaling analyses of terrestrial phenomena and processes, but also to deal with challenges encountered in quantitative spatial reasoning studies. For understanding the spatiotemporal characteristics of terrestrial phenomena and processes, the author provides morphological approaches and algorithms to: Retrieve unique geomorphologic networks and certain terrestrial features Analyze various geomorphological phenomena and processes via a host of scaling laws and the scale-invariant but shape-dependent indices Simulate the fractal-skeletal-based channel network model and the behavioral phases of geomorphologic systems based on the interplay between numeric and graphic analyses Detect strategically significant sets and directional relationships via quantitative spatial reasoning Visualize spatiotemporal behavior and generate contiguous maps via spatial interpolation Incorporating peer-reviewed content, this book offers simple explanations that enable readers—even those with no background in mathematical morphology—to understand the material. It also includes easy-to-follow equations and many helpful illustrations that encourage readers to implement the ideas.

A Guide to Doing Statistics in Second Language Research Using SPSS

Author: Jenifer Larson-Hall

Publisher: Routledge

ISBN: 1135594732

Category: Education

Page: 426

View: 5016


This valuable book shows second language researchers how to use the statistical program SPSS to conduct statistical tests frequently done in SLA research. Using data sets from real SLA studies, A Guide to Doing Statistics in Second Language Research Using SPSS shows newcomers to both statistics and SPSS how to generate descriptive statistics, how to choose a statistical test, and how to conduct and interpret a variety of basic statistical tests. It covers the statistical tests that are most commonly used in second language research, including chi-square, t-tests, correlation, multiple regression, ANOVA and non-parametric analogs to these tests. The text is abundantly illustrated with graphs and tables depicting actual data sets, and exercises throughout the book help readers understand concepts (such as the difference between independent and dependent variables) and work out statistical analyses. Answers to all exercises are provided on the book’s companion website, along with sample data sets and other supplementary material.

Clinical Trials in Oncology, Third Edition

Author: Stephanie Green,Jacqueline Benedetti,Angela Smith,John Crowley

Publisher: CRC Press

ISBN: 1439814481

Category: Mathematics

Page: 264

View: 6157


The third edition of the bestselling Clinical Trials in Oncology provides a concise, nontechnical, and thoroughly up-to-date review of methods and issues related to cancer clinical trials. The authors emphasize the importance of proper study design, analysis, and data management and identify the pitfalls inherent in these processes. In addition, the book has been restructured to have separate chapters and expanded discussions on general clinical trials issues, and issues specific to Phases I, II, and III. New sections cover innovations in Phase I designs, randomized Phase II designs, and overcoming the challenges of array data. Although this book focuses on cancer trials, the same issues and concepts are important in any clinical setting. As always, the authors use clear, lucid prose and a multitude of real-world examples to convey the principles of successful trials without the need for a strong statistics or mathematics background. Armed with Clinical Trials in Oncology, Third Edition, clinicians and statisticians can avoid the many hazards that can jeopardize the success of a trial.

MATLAB® Recipes for Earth Sciences

Author: Martin Trauth

Publisher: Springer

ISBN: 3662462443

Category: Science

Page: 427

View: 7010


MATLAB® is used for a wide range of applications in geosciences, such as image processing in remote sensing, the generation and processing of digital elevation models and the analysis of time series. This book introduces methods of data analysis in geosciences using MATLAB, such as basic statistics for univariate, bivariate and multivariate datasets, time-series analysis, signal processing, the analysis of spatial and directional data and image analysis. The revised and updated Fourth Edition includes sixteen new sections and most chapters have greatly been expanded so that they now include a step by step discussion of all methods before demonstrating the methods with MATLAB functions. New sections include: Array Manipulation; Control Flow; Creating Graphical User Interfaces; Hypothesis Testing; Kolmogorov-Smirnov Test; Mann-Whitney Test; Ansari-Bradley Test; Detecting Abrupt Transitions in Time Series; Exporting 3D Graphics to Create Interactive Documents; Importing, Processing and Exporting LANDSAT Images; Importing and Georeferencing TERRA ASTER Images; Processing and Exporting EO-1 Hyperion Images; Image Enhancement; Correction and Rectification; Shape-Based Object Detection in Images; Discriminant Analysis; and Multiple Linear Regression. The text includes numerous examples demonstrating how MATLAB can be used on data sets from earth sciences. The book’s supplementary electronic material (available online through Springer Link) includes recipes that include all the MATLAB commands featured in the book and the example data.

Statistical Methods in Healthcare

Author: Frederick Faltin,Ron S. Kenett,Fabrizio Ruggeri

Publisher: John Wiley & Sons

ISBN: 1119942047

Category: Medical

Page: 520

View: 2269


In recent years the number of innovative medicinal products and devices submitted and approved by regulatory bodies has declined dramatically. The medical product development process is no longer able to keep pace with increasing technologies, science and innovations and the goal is to develop new scientific and technical tools and to make product development processes more efficient and effective. Statistical Methods in Healthcare focuses on the application of statistical methodologies to evaluate promising alternatives and to optimize the performance and demonstrate the effectiveness of those that warrant pursuit is critical to success. Statistical methods used in planning, delivering and monitoring health care, as well as selected statistical aspects of the development and/or production of pharmaceuticals and medical devices are also addressed. With a focus on finding solutions to these challenges, this book: Provides a comprehensive, in-depth treatment of statistical methods in healthcare, along with a reference source for practitioners and specialists in health care and drug development. Offers a broad coverage of standards and established methods through leading edge techniques. Uses an integrated, case-study based approach, with focus on applications. Looks at the use of analytical and monitoring schemes to evaluate therapeutic performance. Features the application of modern quality management systems to clinical practice, and to pharmaceutical development and production processes. Addresses the use of modern Statistical methods such as Adaptive Design, Seamless Design, Data Mining, Bayesian networks and Bootstrapping that can be applied to support the challenging new vision. Practitioners in healthcare-related professions, ranging from clinical trials to care delivery to medical device design, as well as statistical researchers in the field, will benefit from this book.

Differential Geometry and Statistics

Author: M.K. Murray

Publisher: Routledge

ISBN: 1351455117

Category: Mathematics

Page: 288

View: 9905


Several years ago our statistical friends and relations introduced us to the work of Amari and Barndorff-Nielsen on applications of differential geometry to statistics. This book has arisen because we believe that there is a deep relationship between statistics and differential geometry and moreoever that this relationship uses parts of differential geometry, particularly its 'higher-order' aspects not readily accessible to a statistical audience from the existing literature. It is, in part, a long reply to the frequent requests we have had for references on differential geometry! While we have not gone beyond the path-breaking work of Amari and Barndorff- Nielsen in the realm of applications, our book gives some new explanations of their ideas from a first principles point of view as far as geometry is concerned. In particular it seeks to explain why geometry should enter into parametric statistics, and how the theory of asymptotic expansions involves a form of higher-order differential geometry. The first chapter of the book explores exponential families as flat geometries. Indeed the whole notion of using log-likelihoods amounts to exploiting a particular form of flat space known as an affine geometry, in which straight lines and planes make sense, but lengths and angles are absent. We use these geometric ideas to introduce the notion of the second fundamental form of a family whose vanishing characterises precisely the exponential families.

Encyclopedia of Information Science and Technology, Third Edition

Author: Khosrow-Pour, Mehdi

Publisher: IGI Global

ISBN: 1466658894

Category: Computers

Page: 10384

View: 8623


"This 10-volume compilation of authoritative, research-based articles contributed by thousands of researchers and experts from all over the world emphasized modern issues and the presentation of potential opportunities, prospective solutions, and future directions in the field of information science and technology"--Provided by publisher.

Statistical Analysis

Microsoft Excel 2016

Author: Conrad Carlberg

Publisher: Que Publishing

ISBN: 0134840488

Category: Business & Economics

Page: 576

View: 4751


USE EXCEL’S STATISTICAL TOOLS TO TRANSFORM YOUR DATA INTO KNOWLEDGE Nationally recognized Excel expert Conrad Carlberg shows you how to use Excel 2016 to perform core statistical tasks every business professional, student, and researcher should master. Using real-world examples and downloadable workbooks, Carlberg helps you choose the right technique for each problem and get the most out of Excel’s statistical features. Along the way, he clarifies confusing statistical terminology and helps you avoid common mistakes. You’ll learn how to use correlation and regression, analyze variance and covariance, and test statistical hypotheses using the normal, binomial, t, and F distributions. To help you make accurate inferences based on samples from a population, Carlberg offers insightful coverage of crucial topics ranging from experimental design to the statistical power of F tests. Updated for Excel 2016, this guide covers both modern consistency functions and legacy compatibility functions. Becoming an expert with Excel statistics has never been easier! In this book, you’ll find crystal-clear instructions, insider insights, and complete step-by-step guidance. Master Excel’s most useful descriptive and inferential statistical tools Understand how values cluster together or disperse, and how variables move or classify jointly Tell the truth with statistics—and recognize when others don’t Infer a population’s characteristics from a sample’s frequency distribution Explore correlation and regression to learn how variables move in tandem Use Excel consistency functions such as STDEV.S( ) and STDEV.P( ) Test differences between two means using z tests, t tests, and Excel’s Data Analysis Add-in Identify skewed distributions using Excel’s new built-in box-and-whisker plots and histograms Evaluate statistical power and control risk Explore how randomized block and split plot designs alter the derivation of F-ratios Use coded multiple regression analysis to perform ANOVA with unbalanced factorial designs Analyze covariance with ANCOVA, and properly use multiple covariance Take advantage of Recommended PivotTables, Quick Analysis, and other Excel 2016 shortcuts

Criminological Research

Understanding Qualitative Methods

Author: Emma Wincup

Publisher: SAGE

ISBN: 1473965489

Category: Social Science

Page: 216

View: 4231


Good research starts with careful planning and a thorough understanding of the research process. The abilities to design a research study and to evaluate those conducted by others are core skills every student of criminology must learn. With guidance from theoretical considerations through the steps of the research process, this book equips you with the necessary tools to carry out a successful, ethical study. This is a completely updated new edition, and it features A new skills-focused chapter on how to evaluate existing qualitative studies and design new ones Rich examples from real research making the ideas and concepts concrete New in-depth case studies on fashion counterfeiting, electronic monitoring and youth justice to illustrate the realities of conducting qualitative research A full discussion of the politics of research, issues of access, ethics and managing risk in the field Thought-provoking exercises reinforce practical research skills This book is the perfect guide to theory and practice for any student undertaking qualitative research on crime or criminal justice.

Handbook of Spatial Statistics

Author: Alan E. Gelfand,Peter Diggle,Peter Guttorp,Montserrat Fuentes

Publisher: CRC Press

ISBN: 9781420072884

Category: Mathematics

Page: 619

View: 3078


Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters. The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters. By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.

Measurement Error and Misclassification in Statistics and Epidemiology

Impacts and Bayesian Adjustments

Author: Paul Gustafson

Publisher: CRC Press

ISBN: 0203502760

Category: Mathematics

Page: 200

View: 621


Mismeasurement of explanatory variables is a common hazard when using statistical modeling techniques, and particularly so in fields such as biostatistics and epidemiology where perceived risk factors cannot always be measured accurately. With this perspective and a focus on both continuous and categorical variables, Measurement Error and Misclassification in Statistics and Epidemiology: Impacts and Bayesian Adjustments examines the consequences and Bayesian remedies in those cases where the explanatory variable cannot be measured with precision. The author explores both measurement error in continuous variables and misclassification in discrete variables, and shows how Bayesian methods might be used to allow for mismeasurement. A broad range of topics, from basic research to more complex concepts such as "wrong-model" fitting, make this a useful research work for practitioners, students and researchers in biostatistics and epidemiology."