Download or read book Scan Statistics written by Joseph Glaz and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: In many statistical applications, scientists have to analyze the occurrence of observed clusters of events in time or space. Scientists are especially interested in determining whether an observed cluster of events has occurred by chance if it is assumed that the events are distributed independently and uniformly over time or space. Scan statistics have relevant applications in many areas of science and technology including geology, geography, medicine, minefield detection, molecular biology, photography, quality control and reliability theory and radio-optics.
Download or read book Data Clustering Theory Algorithms and Applications Second Edition written by Guojun Gan and published by SIAM. This book was released on 2020-11-10 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
Download or read book Theory of Spatial Statistics written by M.N.M. van Lieshout and published by CRC Press. This book was released on 2019-03-19 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, real-life examples and theoretical exercises. Solutions to the latter are available in an appendix. Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers. Features * Presents the mathematical foundations of spatial statistics. * Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology. * Gives pointers to the literature to facilitate further study. * Provides example code in R to encourage the student to experiment. * Offers exercises and their solutions to test and deepen understanding. The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
Download or read book Scan Statistics and Applications written by Joseph Glaz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: The study of scan statistics and their applications to many different scientific and engineering problems have received considerable attention in the literature recently. In addition to challenging theoretical problems, the area of scan statis tics has also found exciting applications in diverse disciplines such as archaeol ogy, astronomy, epidemiology, geography, material science, molecular biology, reconnaissance, reliability and quality control, sociology, and telecommunica tion. This will be clearly evident when one goes through this volume. In this volume, we have brought together a collection of experts working in this area of research in order to review some of the developments that have taken place over the years and also to present their new works and point out some open problems. With this in mind, we selected authors for this volume with some having theoretical interests and others being primarily concerned with applications of scan statistics. Our sincere hope is that this volume will thus provide a comprehensive survey of all the developments in this area of research and hence will serve as a valuable source as well as reference for theoreticians and applied researchers. Graduate students interested in this area will find this volume to be particularly useful as it points out many open challenging problems that they could pursue. This volume will also be appropriate for teaching a graduate-level special course on this topic.
Download or read book Runs and Scans with Applications written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert practical and theoretical coverage of runs and scans This volume presents both theoretical and applied aspects of runs and scans, and illustrates their important role in reliability analysis through various applications from science and engineering. Runs and Scans with Applications presents new and exciting content in a systematic and cohesive way in a single comprehensive volume, complete with relevant approximations and explanations of some limit theorems. The authors provide detailed discussions of both classical and current problems, such as: * Sooner and later waiting time * Consecutive systems * Start-up demonstration testing in life-testing experiments * Learning and memory models * "Match" in genetic codes Runs and Scans with Applications offers broad coverage of the subject in the context of reliability and life-testing settings and serves as an authoritative reference for students and professionals alike.
Download or read book Distribution Theory of Runs and Patterns and Its Applications written by James C. Fu and published by World Scientific. This book was released on 2003 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: A rigorous, comprehensive introduction to the finite Markov chain imbedding technique for studying the distributions of runs and patterns from a unified and intuitive viewpoint, away from the lines of traditional combinatorics.
Download or read book Statistical Parametric Mapping The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible
Download or read book Scan Statistics and Applications written by Joseph Glaz and published by Springer Science & Business Media. This book was released on 1999-09 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scan statistics are used in many areas of science and technology to analyze the occurence of observed clusters of events in time and space. The goal is to determine whether an observed cluster of events occurred by chance if it is assumed that the observed events follow a specified probability model. Scan Statistics and Applications is a comprehensive, edited survey that brings together the work of leading authorities to present the most current advances in theory and methodology for this new area of statistical research and application. The chapters contain broad coverage of theory and new analytical and computational methods and techniques in four categories: introductory survey, discrete scan statistics, continuous scan statistics, and applications. Features and Topics:* Comprehensive introductory survey chapter* Discrete scan statistics* Finite Markov chain imbedding* Continuous scan statistics* Spatial scan statistics* Applications in DNA sequence analysis* Monte Carlo approaches to testing order statistics and spacing The book is a valuable resource and state-of-the-art reference for all practitioners, researchers, and professionals in applied probability and statistics who use scan statistics in their work.nbsp;
Download or read book Introduction to the Theory and Application of Data Envelopment Analysis written by Emmanuel Thanassoulis and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: 1 DATA ENVELOPMENT ANALYSIS Data Envelopment Analysis (DEA) was initially developed as a method for assessing the comparative efficiencies of organisational units such as the branches of a bank, schools, hospital departments or restaurants. The key in each case is that they perform feature which makes the units comparable the same function in terms of the kinds of resource they use and the types of output they produce. For example all bank branches to be compared would typically use staff and capital assets to effect income generating activities such as advancing loans, selling financial products and carrying out banking transactions on behalf of their clients. The efficiencies assessed in this context by DEA are intended to reflect the scope for resource conservation at the unit being assessed without detriment to its outputs, or alternatively, the scope for output augmentation without additional resources. The efficiencies assessed are comparative or relative because they reflect scope for resource conservation or output augmentation at one unit relative to other comparable benchmark units rather than in some absolute sense. We resort to relative rather than absolute efficiencies because in most practical contexts we lack sufficient information to derive the superior measures of absolute efficiency. DEA was initiated by Charnes Cooper and Rhodes in 1978 in their seminal paper Chames et al. (1978). The paper operationalised and extended by means of linear programming production economics concepts of empirical efficiency put forth some twenty years earlier by Farrell (1957).
Download or read book Principles of Statistics written by M. G. Bulmer and published by Courier Corporation. This book was released on 2012-04-26 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concise description of classical statistics, from basic dice probabilities to modern regression analysis. Equal stress on theory and applications. Moderate difficulty; only basic calculus required. Includes problems with answers.
Download or read book Methods and Applications of Statistics in the Life and Health Sciences written by Narayanaswamy Balakrishnan and published by John Wiley & Sons. This book was released on 2009-12-02 with total page 1027 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inspired by the Encyclopedia of Statistical Sciences, Second Edition, this volume outlines the statistical tools for successfully working with modern life and health sciences research Data collection holds an essential part in dictating the future of health sciences and public health, as the compilation of statistics allows researchers and medical practitioners to monitor trends in health status, identify health problems, and evaluate the impact of health policies and programs. Methods and Applications of Statistics in the Life and Health Sciences serves as a single, one-of-a-kind resource on the wide range of statistical methods, techniques, and applications that are applied in modern life and health sciences in research. Specially designed to present encyclopedic content in an accessible and self-contained format, this book outlines thorough coverage of the underlying theory and standard applications to research in related disciplines such as biology, epidemiology, clinical trials, and public health. Uniquely combining established literature with cutting-edge research, this book contains classical works and more than twenty-five new articles and completely revised contributions from the acclaimed Encyclopedia of Statistical Sciences, Second Edition. The result is a compilation of more than eighty articles that explores classic methodology and new topics, including: Sequential methods in biomedical research Statistical measures of human quality of life Change-point methods in genetics Sample size determination for clinical trials Mixed-effects regression models for predicting pre-clinical disease Probabilistic and statistical models for conception Statistical methods are explored and applied to population growth, disease detection and treatment, genetic and genomic research, drug development, clinical trials, screening and prevention, and the assessment of rehabilitation, recovery, and quality of life. These topics are explored in contributions written by more than 100 leading academics, researchers, and practitioners who utilize various statistical practices, such as election bias, survival analysis, missing data techniques, and cluster analysis for handling the wide array of modern issues in the life and health sciences. With its combination of traditional methodology and newly developed research, Methods and Applications of Statistics in the Life and Health Sciences has everything students, academics, and researchers in the life and health sciences need to build and apply their knowledge of statistical methods and applications.
Download or read book Learning Statistics with R written by Daniel Navarro and published by Lulu.com. This book was released on 2013-01-13 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
Download or read book Using R for Introductory Statistics written by John Verzani and published by CRC Press. This book was released on 2018-10-03 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of a bestselling textbook, Using R for Introductory Statistics guides students through the basics of R, helping them overcome the sometimes steep learning curve. The author does this by breaking the material down into small, task-oriented steps. The second edition maintains the features that made the first edition so popular, while updating data, examples, and changes to R in line with the current version. See What’s New in the Second Edition: Increased emphasis on more idiomatic R provides a grounding in the functionality of base R. Discussions of the use of RStudio helps new R users avoid as many pitfalls as possible. Use of knitr package makes code easier to read and therefore easier to reason about. Additional information on computer-intensive approaches motivates the traditional approach. Updated examples and data make the information current and topical. The book has an accompanying package, UsingR, available from CRAN, R’s repository of user-contributed packages. The package contains the data sets mentioned in the text (data(package="UsingR")), answers to selected problems (answers()), a few demonstrations (demo()), the errata (errata()), and sample code from the text. The topics of this text line up closely with traditional teaching progression; however, the book also highlights computer-intensive approaches to motivate the more traditional approach. The authors emphasize realistic data and examples and rely on visualization techniques to gather insight. They introduce statistics and R seamlessly, giving students the tools they need to use R and the information they need to navigate the sometimes complex world of statistical computing.
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Download or read book The Book of R written by Tilman M. Davies and published by No Starch Press. This book was released on 2016-07-16 with total page 833 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Download or read book Understanding Machine Learning written by Shai Shalev-Shwartz and published by Cambridge University Press. This book was released on 2014-05-19 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
Download or read book Selected Papers of Frederick Mosteller written by Stephen E. Fienberg and published by Springer Science & Business Media. This book was released on 2007-02-01 with total page 651 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of the best known statisticians of the 20th century, Frederick Mosteller has inspired numerous statisticians and other scientists by his creative approach to statistics and its applications. This volume collects 40 of his most original and influential papers, capturing the variety and depth of his writings. It is hoped that sharing these writings with a new generation of researchers will inspire them to build upon his insights and efforts.
