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| statistical analysis of circular data fisher: Statistical Analysis of Circular Data N. I. Fisher, 1995-10-12 A unified, up-to-date account of circular data-handling techniques, useful throughout science. |
| statistical analysis of circular data fisher: Directional Statistics Kanti V. Mardia, Peter E. Jupp, 2009-09-25 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. |
| statistical analysis of circular data fisher: Applied Directional Statistics Christophe Ley, Thomas Verdebout, 2018-09-03 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. |
| statistical analysis of circular data fisher: Directional and Multivariate Statistics Somesh Kumar, Barry C. Arnold, Kunio Shimizu, Arnab Kumar Laha, 2025-05-05 This book contains select chapters on a range of topics in directional statistics, multivariate statistical inference, financial statistics, statistical machine learning and reliability inference. At the 43rd Annual Convention of the Indian Society for Probability and Statistics (ISPS) held in Prayagraj (formerly Allahabad), Uttar Pradesh, India, from 6–8 February 2024, attribute was paid to Prof. Ashis SenGupta on the occasion of his 70th birthday. He has pioneered research on directional statistics in the modern era in India and enhanced it worldwide and contributed significantly to the advancement of the following topics: Highly flexible distributions on manifolds Statistical machine learning in data science Big data on manifolds Optimal multiparameter, multivariate statistical inference Reliability inference and stress-dependent-strength models Directional statistics for highly volatile financial models Cylindrical, spherical and toroidal regression analysis Innovative applications of emerging real-life directional data |
| statistical analysis of circular data fisher: Topics in Circular Statistics S. Rao Jammalamadaka, Ambar Sengupta, Ashis Sengupta, 2001 This research monograph on circular data analysis covers some recent advances in the field, besides providing a brief introduction to, and a review of, existing methods and models. The primary focus is on recent research into topics such as change-point problems, predictive distributions, circular correlation and regression, etc. An important feature of this work is the S-plus subroutines provided for analyzing actual data sets. Coupled with the discussion of new theoretical research, the book should benefit both the researcher and the practitioner. Contents: Circular Probability Distributions; Some Sampling Distributions; Estimation of Parameters; Tests for Mean Direction and Concentration; Tests for Uniformity; Nonparametric Testing Procedures; Circular Correlation and Regression; Predictive Inference for Directional Data; Outliers and Related Problems; Change-Point Problems; Miscellaneous Topics; Some Facts on Bessel Functions; How to Use the CircStats Package. Readership: Researchers and practitioners dealing with circular data. |
| statistical analysis of circular data fisher: Statistical Analysis Handbook Dr Michael John de Smith, A Comprehensive Handbook of Statistical Concepts, Techniques and Software Tools. |
| statistical analysis of circular data fisher: Circular Statistics in R Arthur Pewsey, Markus Neuhäuser, Graeme D Ruxton, 2013-09-26 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 fisher: Design and Analysis of Experiments, Volume 3 Klaus Hinkelmann, 2012-02-14 Provides timely applications, modifications, and extensions of experimental designs for a variety of disciplines Design and Analysis of Experiments, Volume 3: Special Designs and Applications continues building upon the philosophical foundations of experimental design by providing important, modern applications of experimental design to the many fields that utilize them. The book also presents optimal and efficient designs for practice and covers key topics in current statistical research. Featuring contributions from leading researchers and academics, the book demonstrates how the presented concepts are used across various fields from genetics and medicinal and pharmaceutical research to manufacturing, engineering, and national security. Each chapter includes an introduction followed by the historical background as well as in-depth procedures that aid in the construction and analysis of the discussed designs. Topical coverage includes: Genetic cross experiments, microarray experiments, and variety trials Clinical trials, group-sequential designs, and adaptive designs Fractional factorial and search, choice, and optimal designs for generalized linear models Computer experiments with applications to homeland security Robust parameter designs and split-plot type response surface designs Analysis of directional data experiments Throughout the book, illustrative and numerical examples utilize SAS®, JMP®, and R software programs to demonstrate the discussed techniques. Related data sets and software applications are available on the book's related FTP site. Design and Analysis of Experiments, Volume 3 is an ideal textbook for graduate courses in experimental design and also serves as a practical, hands-on reference for statisticians and researchers across a wide array of subject areas, including biological sciences, engineering, medicine, and business. |
| statistical analysis of circular data fisher: Quantitative Ecology and Evolutionary Biology Otso Ovaskainen, Henrik Johan de Knegt, Maria del Mar Delgado, 2016 This is an integration of empirical data and theory in quantitative ecology and evolution through the use of mathematical models and statistical methods. |
| statistical analysis of circular data fisher: Nonparametric Inference on Manifolds Abhishek Bhattacharya, Rabi Bhattacharya, 2012-04-05 Ideal for statisticians, this book will also interest probabilists, mathematicians, computer scientists, and morphometricians with mathematical training. It presents a systematic introduction to a general nonparametric theory of statistics on manifolds, with emphasis on manifolds of shapes. The theory has important applications in medical diagnostics, image analysis and machine vision. |
| statistical analysis of circular data fisher: Geometry Driven Statistics Ian L. Dryden, John T. Kent, 2015-09-28 A timely collection of advanced, original material in the area of statistical methodology motivated by geometric problems, dedicated to the influential work of Kanti V. Mardia This volume celebrates Kanti V. Mardia's long and influential career in statistics. A common theme unifying much of Mardia’s work is the importance of geometry in statistics, and to highlight the areas emphasized in his research this book brings together 16 contributions from high-profile researchers in the field. Geometry Driven Statistics covers a wide range of application areas including directional data, shape analysis, spatial data, climate science, fingerprints, image analysis, computer vision and bioinformatics. The book will appeal to statisticians and others with an interest in data motivated by geometric considerations. Summarizing the state of the art, examining some new developments and presenting a vision for the future, Geometry Driven Statistics will enable the reader to broaden knowledge of important research areas in statistics and gain a new appreciation of the work and influence of Kanti V. Mardia. |
| statistical analysis of circular data fisher: Innovations in Biomolecular Modeling and Simulations Tamar Schlick, 2012-05-24 The chemical and biological sciences face unprecedented opportunities in the 21st century. A confluence of factors from parallel universes - advances in experimental techniques in biomolecular structure determination, progress in theoretical modeling and simulation for large biological systems, and breakthroughs in computer technology - has opened new avenues of opportunity as never before. Now, experimental data can be interpreted and further analysed by modeling, and predictions from any approach can be tested and advanced through companion methodologies and technologies. This two volume set describes innovations in biomolecular modeling and simulation, in both the algorithmic and application fronts. With contributions from experts in the field, the books describe progress and innovation in areas including: simulation algorithms for dynamics and enhanced configurational sampling, force field development, implicit solvation models, coarse-grained models, quantum-mechanical simulations, protein folding, DNA polymerase mechanisms, nucleic acid complexes and simulations, RNA structure analysis and design and other important topics in structural biology modeling. The books are aimed at graduate students and experts in structural biology and chemistry and the emphasis is on reporting innovative new approaches rather than providing comprehensive reviews on each subject. |
| statistical analysis of circular data fisher: Graphics for Statistics and Data Analysis with R Kevin J. Keen, 2018-09-26 Praise for the First Edition The main strength of this book is that it provides a unified framework of graphical tools for data analysis, especially for univariate and low-dimensional multivariate data. In addition, it is clearly written in plain language and the inclusion of R code is particularly useful to assist readers’ understanding of the graphical techniques discussed in the book. ... It not only summarises graphical techniques, but it also serves as a practical reference for researchers and graduate students with an interest in data display. -Han Lin Shang, Journal of Applied Statistics Graphics for Statistics and Data Analysis with R, Second Edition, presents the basic principles of graphical design and applies these principles to engaging examples using the graphics and lattice packages in R. It offers a wide array of modern graphical displays for data visualization and representation. Added in the second edition are coverage of the ggplot2 graphics package, material on human visualization and color rendering in R, on screen, and in print. Features Emphasizes the fundamentals of statistical graphics and best practice guidelines for producing and choosing among graphical displays in R Presents technical details on topics such as: the estimation of quantiles, nonparametric and parametric density estimation; diagnostic plots for the simple linear regression model; polynomial regression, splines, and locally weighted polynomial regression for producing a smooth curve; Trellis graphics for multivariate data Provides downloadable R code and data for figures at www.graphicsforstatistics.com Kevin J. Keen is a Professor of Mathematics and Statistics at the University of Northern British Columbia (Prince George, Canada) and an Accredited Professional StatisticianTM by the Statistical Society of Canada and the American Statistical Association. |
| statistical analysis of circular data fisher: Differential Geometrical Theory of Statistics Frédéric Barbaresco, Frank Nielsen, 2018-04-06 This book is a printed edition of the Special Issue Differential Geometrical Theory of Statistics that was published in Entropy |
| statistical analysis of circular data fisher: Handbook of Mathematical Geosciences B.S. Daya Sagar, Qiuming Cheng, Frits Agterberg, 2018-06-25 This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences. |
| statistical analysis of circular data fisher: Directional Statistics for Innovative Applications Ashis SenGupta, Barry C. Arnold, 2022-06-15 In commemoration of the bicentennial of the birth of the “lady who gave the rose diagram to us”, this special contributed book pays a statistical tribute to Florence Nightingale. This book presents recent phenomenal developments, both in rigorous theory as well as in emerging methods, for applications in directional statistics, in 25 chapters with contributions from 65 renowned researchers from 25 countries. With the advent of modern techniques in statistical paradigms and statistical machine learning, directional statistics has become an indispensable tool. Ranging from data on circles to that on the spheres, tori and cylinders, this book includes solutions to problems on exploratory data analysis, probability distributions on manifolds, maximum entropy, directional regression analysis, spatio-directional time series, optimal inference, simulation, statistical machine learning with big data, and more, with their innovative applications to emerging real-life problems in astro-statistics, bioinformatics, crystallography, optimal transport, statistical process control, and so on. |
| statistical analysis of circular data fisher: Geocomputation Chris Brunsdon, Alex Singleton, 2015-01-22 Geocomputation is the use of software and computing power to solve complex spatial problems. It is gaining increasing importance in the era of the ‘big data’ revolution, of ‘smart cities’, of crowdsourced data, and of associated applications for viewing and managing data geographically - like Google Maps. This student focused book: Provides a selection of practical examples of geocomputational techniques and ‘hot topics’ written by world leading practitioners. Integrates supporting materials in each chapter, such as code and data, enabling readers to work through the examples themselves. Chapters provide highly applied and practical discussions of: Visualisation and exploratory spatial data analysis Space time modelling Spatial algorithms Spatial regression and statistics Enabling interactions through the use of neogeography All chapters are uniform in design and each includes an introduction, case studies, conclusions - drawing together the generalities of the introduction and specific findings from the case study application – and guidance for further reading. This accessible text has been specifically designed for those readers who are new to Geocomputation as an area of research, showing how complex real-world problems can be solved through the integration of technology, data, and geocomputational methods. This is the applied primer for Geocomputation in the social sciences. |
| statistical analysis of circular data fisher: Statistics of Directional Data K. V. Mardia, 2014-07-03 Probability and Mathematical Statistics: A Series of Monographs and Textbooks: Statistics of Directional Data aims to provide a systematic account of statistical theory and methodology for observations which are directions. The publication first elaborates on angular data and frequency distributions, descriptive measures, and basic concepts and theoretical models. Discussions focus on moments and measures of location and dispersion, distribution function, corrections for grouping, calculation of the mean direction and the circular variance, interrelations between different units of angular measurement, and diagrammatical representation. The book then examines fundamental theorems and distribution theory, point estimation, and tests for samples from von Mises populations. The text takes a look at non-parametric tests, distributions on spheres, and inference problems on the sphere. Topics include tests for axial data, point estimation, distribution theory, moments and limiting distributions, and tests of goodness of fit and tests of uniformity. The publication is a dependable reference for researchers interested in probability and mathematical statistics. |
| statistical analysis of circular data fisher: Statistics, Society and Environment J. Andrés Christen, Ruth Fuentes-García, Gabriel Núñez-Antonio, Sergio Pérez, Alan Riva-Palacio, 2025-02-12 This volume features a collection of peer-reviewed contributions from the biannual conference organized by the Mexican Statistical Society, held in Cuernavaca, Mexico, from September 27-29, 2023. Statistical research in Latin America is vibrant and far-reaching, with extensive networks both within the region and beyond. However, much of this work is published in Spanish, limiting access for a broader audience. This volume aims to bridge that gap by presenting selected research from Latin American scholars and their collaborators to a wider readership. Academics will find value in the latest methodological advancements, while practitioners from various fields may discover innovative tools for data analysis. The volume places special emphasis on environmental statistics and applications that address societal issues or directly model social phenomena. |
| statistical analysis of circular data fisher: Correlated Data Analysis: Modeling, Analytics, and Applications Peter X. -K. Song, 2007-06-30 This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas. |
| statistical analysis of circular data fisher: Oceanography Marco Marcelli, 2012-03-23 How inappropriate to call this planet Earth when it is quite clearly Ocean (Arthur C. Clarke). Life has been originated in the oceans, human health and activities depend from the oceans and the world life is modulated by marine and oceanic processes. From the micro-scale, like coastal processes, to macro-scale, the oceans, the seas and the marine life, play the main role to maintain the earth equilibrium, both from a physical and a chemical point of view. Since ancient times, the world's oceans discovery has brought to humanity development and wealth of knowledge, the metaphors of Ulysses and Jason, represent the cultural growth gained through the explorations and discoveries. The modern oceanographic research represents one of the last frontier of the knowledge of our planet, it depends on the oceans exploration and so it is strictly connected to the development of new technologies. Furthermore, other scientific and social disciplines can provide many fundamental inputs to complete the description of the entire ocean ecosystem. Such multidisciplinary approach will lead us to understand the better way to preserve our Blue Planet: the Earth. |
| statistical analysis of circular data fisher: Advances on Methodological and Applied Aspects of Probability and Statistics N. Balakrishnan, 2004-03-01 This is one of two volumes that sets forth invited papers presented at the International Indian Statistical Association Conference. This volume emphasizes advancements in methodology and applications of probability and statistics. The chapters, representing the ideas of vanguard researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing, robust inference, regression and design and sample size methodology. The text also fully describes the applications of these new ideas to industry, ecology, biology, health, economics and management. Researchers and graduate students in mathematical analysis, as well as probability and statistics professionals in industry, will learn much from this volume. |
| statistical analysis of circular data fisher: The Everglades Experiments Curtis Richardson, 2008-03-12 In the late 1960s, I worked as a graduate teaching assistant in plant ecology for the late Dr. John Henry Davis at the University of Florida. On one of our visits to the Everglades, he mentioned to me that he had been studying problems of the Everglades since the early 1930s, and that rapid growth in Florida, unless checked, was about to doom the Everglades. He hoped his vegetation survey of the Everglades and his v- etation map could someday be used to help restore the Everglades to some semblance of what it had been prior to the turn of the century. These long-forgotten discussions with Dr. Davis were rekindled when, during a wetland conference in Orlando, Florida in the late 1980s, I was asked what might be responsible for the reported massive invasion of cattails that had been noted during the past decade in the Everglades. Several hypotheses were presented at the meeting, including some preliminary data on the significant inputs of nutrients from agricultural lands and Lake Okeechobee to the north. The shifts in the hydrologic conditions and flow patterns of the existing Everglades were also mentioned. Because of the extensive work on phosphorus and nutrient retention then being done at the Duke University Wetland Center, I was asked in early 1989 to do a preliminary survey and analysis of the ecological status of the Everglades. From this early work, carried out by Dr. |
| statistical analysis of circular data fisher: Digital Image Processing Wilhelm Burger, Mark J. Burge, 2022-07-23 This modern, self-contained textbook provides an accessible introduction to the field from the perspective of a practicing programmer, supporting a detailed presentation of the fundamental concepts and techniques with practical exercises and fully worked out implementation examples. This much-anticipated 3rd edition of the definitive textbook on Digital Image Processing has been completely revised and expanded with new content, improved illustrations and teaching material. Topics and features: Contains new chapters on fitting of geometric primitives, randomized feature detection (RANSAC), and maximally stable extremal regions (MSER). Includes exercises for most chapters and provides additional supplementary materials and software implementations at an associated website. Uses ImageJ for all examples, a widely used open source imaging environment that can run on all major platforms. Describes each solution in a stepwise manner in mathematical form, as abstract pseudocode algorithms, and as complete Java programs that can be easily ported to other programming languages. Presents suggested outlines for a one- or two-semester course in the preface. Advanced undergraduate and graduate students will find this comprehensive and example-rich textbook will serve as the ideal introduction to digital image processing. It will also prove invaluable to researchers and professionals seeking a practically focused self-study primer. |
| statistical analysis of circular data fisher: Information Processing and Management of Uncertainty in Knowledge-Based Systems Marie-Jeanne Lesot, Susana Vieira, Marek Z. Reformat, João Paulo Carvalho, Fernando Batista, Bernadette Bouchon-Meunier, Ronald R. Yager, 2025-04-30 This book is a collection of papers focused on techniques for managing uncertainty and aggregation. It provides a forum for exchanging ideas between theoreticians and practitioners in these and related areas. The papers are part of the 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, which will occur in Lisbon, Portugal, from July 22 to 26, 2024. The collection describes the latest findings on topics such as advances in fuzzy systems and data analysis, optimization, scheduling via modeling uncertainty, explainability, decision-making, implications, data aggregation, and aggregation operators. A special chapter is dedicated to the memory of Michio Sugeno. The book is a valuable resource for practitioners, researchers, and graduate students who want to apply fuzzy-based techniques to real-world data analysis and management processes involving imprecision and uncertainty. |
| statistical analysis of circular data fisher: Advances in Artificial Intelligence Oscar Luaces, José A. Gámez, Edurne Barrenechea, Alicia Troncoso, Mikel Galar, Héctor Quintián, Emilio Corchado, 2016-09-07 This book constitutes the refereed proceedings of the 16th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2016, held in Salamanca, Spain, in September 2016. The 47 revised full papers presented were carefully selected from 166 submissions. Apart from the presentation of technical full papers, the scientific program of CAEPIA 2016 included an App contest, a Doctoral Consortium and, as a follow-up to the success achieved in previously CAEPIA editions, a special session on outstanding recent papers (Key Works) already published in renowned journals or forums. |
| statistical analysis of circular data fisher: Security and Trust Management Rafael Accorsi, Silvio Ranise, 2013-09-04 This book constitutes the refereed proceedings of the 9th International Workshop on Security and Trust Management, STM 2013, held in Egham, UK, in September 2013 - in conjunction with the 18th European Symposium Research in Computer Security (ESORICS 2013). The 15 revised full papers including two invited talks were carefully reviewed and selected from 47 submissions. The papers are organized into topical sections on policy enforcement and monitoring; access control; trust, reputation, and privacy; distributed systems and physical security; authentication and security policies. |
| statistical analysis of circular data fisher: Geographic Information Wade Bishop, Tony H. Grubesic, 2016-10-27 The history and future of geographic information (GI) in the context of big data creates new avenues of concern over its organization, access and use. In this book the authors explore both the background and present challenges facing the preservation of GI, focusing on the roles of librarians, archivists, data scientists, and other information professionals in the creation of GI records for its organization, access, and use. |
| statistical analysis of circular data fisher: Studies in Housing and Urban Analysis in Japan Yasushi Asami, Yukio Sadahiro, Ikuho Yamada, Kimihiro Hino, 2024-03-06 This book presents research in the field of housing and urban analysis in Japan. It features carefully selected English translations of peer-reviewed articles published in journals in Japan, especially by authors involved in the laboratory supervised by Professor Yasushi Asami. The topics covered include economic analysis of the housing market, analyses of residential environment and human behaviour/psychology, analyses related to urban policies such as intermunicipal cooperation, teleworking and solar photovoltaics installation, spatial analyses of urban entities and effective visualization. Housing and urban analysis has developed using theory and methods in the fields of economics, regional science, geography, statistics, spatial psychology and urban sociology. Even though the methods of analysis differ from chapter to chapter, the ultimate goal of the research is the same. Namely, the target of the research is a better understanding of urban phenomena and effective improvement of urban space and society. The academic contributions in this collection of work are helpful for academics, practitioners and policy makers not only in Japan but also in other Asian countries. |
| statistical analysis of circular data fisher: Systems, Decision and Control in Energy IV Artur Zaporozhets, 2023-03-01 The concept of energy includes methods for obtaining and using various types of energy for the needs of human society. Energy is one of the foundations for the development of modern society. The effectiveness of solving social, economic and technical problems, as well as the anthropogenic transformations of nature, is largely determined by energy production and the scale of energy production.Modern energy is not a separate industry, but it penetrates widely into other areas, in particular, chemical, transport, aerospace, construction, metallurgy, engineering, agriculture, etc. The energy sector is based on complex technical systems that are multicomponent, spatially distributed systems that during their operation are affected to a wide range of design and non-design thermomechanical loading conditions, the effects of aggressive fields and units, unauthorized influences (operator errors, terrorism, sabotage) and can reach various limit states.Complex technical systems are characterized by complex non-linear interactions between their constituent elements, complex chains (scenarios) of cause-effect relationships between hazardous, probabilistic events and processes that occur during their life. These scenarios can be implemented over complex ramified scenario trees.Ensuring the operational reliability, durability and safety of power equipment is a difficult task, which is associated with the organization of the reliability of control over the operation of power plants and ensuring optimal conditions for their operation. In this regard, we can distinguish a whole class of tasks related to the development of control systems, diagnostics and monitoring in the energy industry, which are presented in this book. Of particular relevance now is the use of UAVs in the energy sector.Particular attention must be paid to the environmental consequences of the operation of energy facilities, the main of which is significant environmental pollution in large cities and industrial areas.The development of environmental management information systems is the prerogative of the state, corporations and one of the main directions of the national informatization policy. A clearly debugged system of environmental monitoring gives a general idea of the features of the current ecological state, the main directions of state policy in the field of environmental protection, the use of natural resources and environmental safety. The methodology and hardware-software tools for monitoring the state of the environment presented in the monograph are effective tools for supporting decision-making in managing the environmental safety of the atmosphere during its technogenic pollution. |
| statistical analysis of circular data fisher: Phenological Research Irene L. Hudson, Marie R. Keatley, 2009-11-24 As climate change continues to dominate the international environmental agenda, phenology – the study of the timing of recurring biological events – has received increasing research attention, leading to an emerging consensus that phenology can be viewed as an ‘early warning system’ for climate change impact. A multidisciplinary science involving many branches of ecology, geography and remote sensing, phenology to date has lacked a coherent methodological text. This new synthesis, including contributions from many of the world’s leading phenologists, therefore fills a critical gap in the current biological literature. Providing critiques of current methods, as well as detailing novel and emerging methodologies, the book, with its extensive suite of references, provides readers with an understanding of both the theoretical basis and the potential applications required to adopt and adapt new analytical and design methods. An invaluable source book for researchers and students in ecology and climate change science, the book also provides a useful reference for practitioners in a range of sectors, including human health, fisheries, forestry, agriculture and natural resource management. |
| statistical analysis of circular data fisher: MATLAB® Recipes for Earth Sciences Martin H. Trauth, 2015-02-17 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 analysis of circular data fisher: Sequential Monte Carlo Methods in Practice Arnaud Doucet, Nando de Freitas, Neil Gordon, 2013-03-09 Monte Carlo methods are revolutionising the on-line analysis of data in fields as diverse as financial modelling, target tracking and computer vision. These methods, appearing under the names of bootstrap filters, condensation, optimal Monte Carlo filters, particle filters and survial of the fittest, have made it possible to solve numerically many complex, non-standarard problems that were previously intractable. This book presents the first comprehensive treatment of these techniques, including convergence results and applications to tracking, guidance, automated target recognition, aircraft navigation, robot navigation, econometrics, financial modelling, neural networks,optimal control, optimal filtering, communications, reinforcement learning, signal enhancement, model averaging and selection, computer vision, semiconductor design, population biology, dynamic Bayesian networks, and time series analysis. This will be of great value to students, researchers and practicioners, who have some basic knowledge of probability. Arnaud Doucet received the Ph. D. degree from the University of Paris- XI Orsay in 1997. From 1998 to 2000, he conducted research at the Signal Processing Group of Cambridge University, UK. He is currently an assistant professor at the Department of Electrical Engineering of Melbourne University, Australia. His research interests include Bayesian statistics, dynamic models and Monte Carlo methods. Nando de Freitas obtained a Ph.D. degree in information engineering from Cambridge University in 1999. He is presently a research associate with the artificial intelligence group of the University of California at Berkeley. His main research interests are in Bayesian statistics and the application of on-line and batch Monte Carlo methods to machine learning. |
| statistical analysis of circular data fisher: Angular Statistics A V Dattatreya Rao, S V S Girija, 2019-12-20 Directional data arise in the form of circular / semicircular / axial, symmetric / asymmetric, uni / bimodal data, in practical situations of varied fields. For the purpose of modeling such kind of data sets, the data scientists found that existing models as inadequate. As there is paucity of angular models, and to fill the gap, this book is designed at constructing new angular models with the existing techniques and to develop new tools of constructing angular models with an application to control charts in angular models. This book is planned to cover the following topics in nine chapters Wrapped, stereographic and offset circular models Construction of angular models using Rising Sun function, positive definite sequences, discretization and through differential approach Extemporaneous Semicircular / arc and asymmetric l – axial models Choice of angular models as an inferential aspect and construction of control charts for angular data as an application are presented. This graduate level book will be useful for data scientists, researchers and research students of Statistics and allied fields. |
| statistical analysis of circular data fisher: Directional Estimation for Robotic Beating Heart Surgery Kurz, Gerhard, 2015-05-26 In robotic beating heart surgery, a remote-controlled robot can be used to carry out the operation while automatically canceling out the heart motion. The surgeon controlling the robot is shown a stabilized view of the heart. First, we consider the use of directional statistics for estimation of the phase of the heartbeat. Second, we deal with reconstruction of a moving and deformable surface. Third, we address the question of obtaining a stabilized image of the heart. |
| statistical analysis of circular data fisher: Text Mining Ashok N. Srivastava, Mehran Sahami, 2009-06-15 The Definitive Resource on Text Mining Theory and Applications from Foremost Researchers in the FieldGiving a broad perspective of the field from numerous vantage points, Text Mining: Classification, Clustering, and Applications focuses on statistical methods for text mining and analysis. It examines methods to automatically cluster and classify te |
| statistical analysis of circular data fisher: Trends and Applications in Knowledge Discovery and Data Mining Jiuyong Li, Longbing Cao, Can Wang, Kay Chen Tan, Bo Liu, Jian Pei, Vincent S. Tseng, 2013-08-23 This book constitutes the refereed proceedings at PAKDD Workshops 2013, affiliated with the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) held in Gold Coast, Australia in April 2013. The 47 revised full papers presented were carefully reviewed and selected from 92 submissions. The workshops affiliated with PAKDD 2013 include: Data Mining Applications in Industry and Government (DMApps), Data Analytics for Targeted Healthcare (DANTH), Quality Issues, Measures of Interestingness and Evaluation of Data Mining Models (QIMIE), Biologically Inspired Techniques for Data Mining (BDM), Constraint Discovery and Application (CDA), Cloud Service Discovery (CloudSD). |
| statistical analysis of circular data fisher: Statistics for Earth and Environmental Scientists John H. Schuenemeyer, Lawrence J. Drew, 2011-04-12 A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analytic tools and shows readers how to apply them to real-world problems. The authors present several different statistical approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, and sampling—all of which are explored through case studies that use real data from earth science applications. Subsequent chapters focus on principles of modeling and the key methods and techniques for analyzing scientific data, including: Interval estimation and Methods for analyzinghypothesis testing of means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept and application, given as equations, and then accompanied by heuristic justification rather than a formal proof. Data analysis, model building, and statistical inference are stressed throughout, and readers are encouraged to collect their own data to incorporate into the exercises at the end of each chapter. Most data sets, graphs, and analyses are computed using R, but can be worked with using any statistical computing software. A related website features additional data sets, answers to selected exercises, and R code for the book's examples. Statistics for Earth and Environmental Scientists is an excellent book for courses on quantitative methods in geology, geography, natural resources, and environmental sciences at the upper-undergraduate and graduate levels. It is also a valuable reference for earth scientists, geologists, hydrologists, and environmental statisticians who collect and analyze data in their everyday work. |
| statistical analysis of circular data fisher: Handbook of Digital Human Modeling Vincent G. Duffy, 2016-04-19 The rapid introduction of sophisticated computers, services, telecommunications systems, and manufacturing systems has caused a major shift in the way people use and work with technology. It is not surprising that computer-aided modeling has emerged as a promising method for ensuring products meet the requirements of the consumer. The Handbook of D |
| statistical analysis of circular data fisher: Modern Directional Statistics Christophe Ley, Thomas Verdebout, 2017-08-03 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. |
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a sentence.
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical analysis. The generalizations are advanced on the basis of statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative data, or a label, as with …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background circumstances” or statistical …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of different ways to …
Statistics | Definition, Types, & Importance | Britannica
May 20, 2025 · statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic activities …
Statistical - definition of statistical by The Free Dictionary
Define statistical. statistical synonyms, statistical pronunciation, statistical translation, English dictionary definition of statistical. adj. Of, relating to, or employing statistics or the principles of …
STATISTICAL definition and meaning | Collins English Dictionary
Statistical means relating to the use of statistics. The report contains a great deal of statistical information. Of or relating to statistics.... Click for English pronunciations, examples sentences, …
Introduction to Research Statistical Analysis: An Overview of the ...
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power.
Statistics - Definition, Examples, Mathematical Statistics
Statistics is defined as the process of collection of data, classifying data, representing the data for easy interpretation, and further analysis of data. Statistics also is referred to as arriving at …
STATISTICAL Definition & Meaning - Merriam-Webster
The meaning of STATISTICAL is of, relating to, based on, or employing the principles of statistics. How to use statistical in a sentence.
STATISTICAL | English meaning - Cambridge Dictionary
There is very little statistical evidence. It was designed to facilitate the combination of qualitative methods with statistical analysis. The generalizations are advanced on the basis of statistical …
Statistics - Wikipedia
Statistics is the discipline that deals with data, facts and figures with which meaningful information is inferred. Data may represent a numerical value, in form of quantitative data, or a label, as …
STATISTICAL Definition & Meaning | Dictionary.com
of, pertaining to, consisting of, or based on statistics. statistics. Examples have not been reviewed. In doing so, the judges said she could not point to “background circumstances” or …
What is Statistical Analysis? - GeeksforGeeks
Apr 15, 2025 · Statistical Analysis means gathering, understanding, and showing data to find patterns and connections that can help us make decisions. It includes lots of different ways to …
Statistics | Definition, Types, & Importance | Britannica
May 20, 2025 · statistics, the science of collecting, analyzing, presenting, and interpreting data. Governmental needs for census data as well as information about a variety of economic …
Statistical - definition of statistical by The Free Dictionary
Define statistical. statistical synonyms, statistical pronunciation, statistical translation, English dictionary definition of statistical. adj. Of, relating to, or employing statistics or the principles of …
STATISTICAL definition and meaning | Collins English Dictionary
Statistical means relating to the use of statistics. The report contains a great deal of statistical information. Of or relating to statistics.... Click for English pronunciations, examples sentences, …
Introduction to Research Statistical Analysis: An Overview of the ...
This article covers many statistical ideas essential to research statistical analysis. Sample size is explained through the concepts of statistical significance level and power.
Statistics - Definition, Examples, Mathematical Statistics
Statistics is defined as the process of collection of data, classifying data, representing the data for easy interpretation, and further analysis of data. Statistics also is referred to as arriving at …
