Download or read book Statistical Paradigms Recent Advances And Reconciliations written by Ashis Sengupta and published by World Scientific. This book was released on 2014-10-03 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Statistical Evidence written by Richard Royall and published by Routledge. This book was released on 2017-11-22 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Interpreting statistical data as evidence, Statistical Evidence: A Likelihood Paradigm focuses on the law of likelihood, fundamental to solving many of the problems associated with interpreting data in this way. Statistics has long neglected this principle, resulting in a seriously defective methodology. This book redresses the balance, explaining why science has clung to a defective methodology despite its well-known defects. After examining the strengths and weaknesses of the work of Neyman and Pearson and the Fisher paradigm, the author proposes an alternative paradigm which provides, in the law of likelihood, the explicit concept of evidence missing from the other paradigms. At the same time, this new paradigm retains the elements of objective measurement and control of the frequency of misleading results, features which made the old paradigms so important to science. The likelihood paradigm leads to statistical methods that have a compelling rationale and an elegant simplicity, no longer forcing the reader to choose between frequentist and Bayesian statistics.

Download or read book Research Paradigms and Their Methodological Alignment in Social Sciences written by Bunmi Isaiah Omodan and published by Taylor & Francis. This book was released on 2024-08-01 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research Paradigms and Their Methodological Alignment in Social Sciences is a comprehensive guide addressing the common conceptions surrounding research paradigms. This practical book demystifies complex concepts, giving researchers a nuanced understanding of the significance of research paradigms. It offers detailed insights, examples, and strategies for selecting and applying appropriate research methods, aiming to enhance the rigour and impact of scholarly work. This insightful guide meticulously explores the intricacies of research paradigms in the social sciences. It begins by unravelling the concept and historical development of research paradigm, emphasising its pivotal role in shaping the research process. The book elucidates major research paradigms, including positivism, interpretivism, transformative paradigm, postcolonial indigenous paradigm, and pragmatism. Each paradigm is dissected, unveiling philosophical underpinnings, methodological designs, and critical considerations. The chapters carefully align research questions with specific paradigms through illustrative case studies, offering practical guidance for researchers at all levels. Notably, the transformative paradigm and postcolonial indigenous perspective receive dedicated attention, addressing their unique methodological nuances and ethical dimensions. The exploration extends to pragmatism, seamlessly integrating theoretical foundations with real-world applications. The book strives to bridge the awareness gap in academic settings, fostering a profound appreciation for research paradigms and promoting a thoughtful, rigorous approach to scholarly inquiry. This book caters to students, novice and experienced researchers, offering a comprehensive understanding of research paradigms. It's valuable for academia, aiding undergraduate and postgraduate students, educators, and researchers in various disciplines. Research organisations, academic institutions, and professionals in diverse fields engaged in research and development will also find it a valuable resource.

Download or read book Christian and Humanist Foundations for Statistical Inference written by Andrew M. Hartley and published by Wipf and Stock Publishers. This book was released on 2007-12-01 with total page 138 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Philosophy of the Law Idea (PLI) analyzes the manner in which religious beliefs control scientific theorizing. Religious beliefs control philosophical overviews of reality. Overviews of reality, also called ontologies, try to discover and disclose the essential nature of reality. They are concerned with what kinds of things exist and with the connections between the various types of properties and laws in human experience. Among such overviews are the biblically consistent overview provided by the PLI and certain humanist "mathematicist" and "subjectivist" overviews. The science of statistical inference seeks to evaluate the credibility of scientific hypotheses given empirical data. This essay reviews various popular paradigms, or systems of theories, concerning the ways that credibility may be evaluated, and identifies some ways that these religiously controlled overviews of reality have, in turn, controlled statistical paradigms. In particular, one paradigm harmonizes with the PLI's overview; another, with the subjectivist overview; and two others, with the mathematicist overview.

Download or read book Statistical Evidence written by Richard M. Royall and published by . This book was released on 1997 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Philosophy of Statistics written by and published by Elsevier. This book was released on 2011-05-31 with total page 1253 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statisticians and philosophers of science have many common interests but restricted communication with each other. This volume aims to remedy these shortcomings. It provides state-of-the-art research in the area of philosophy of statistics by encouraging numerous experts to communicate with one another without feeling “restricted by their disciplines or thinking “piecemeal in their treatment of issues. A second goal of this book is to present work in the field without bias toward any particular statistical paradigm. Broadly speaking, the essays in this Handbook are concerned with problems of induction, statistics and probability. For centuries, foundational problems like induction have been among philosophers’ favorite topics; recently, however, non-philosophers have increasingly taken a keen interest in these issues. This volume accordingly contains papers by both philosophers and non-philosophers, including scholars from nine academic disciplines. Provides a bridge between philosophy and current scientific findings Covers theory and applications Encourages multi-disciplinary dialogue

Download or read book Utilizing Big Data Paradigms for Business Intelligence written by Darmont, Jérôme and published by IGI Global. This book was released on 2018-08-10 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because efficient compilation of information allows managers and business leaders to make the best decisions for the financial solvency of their organizations, data analysis is an important part of modern business administration. Understanding the use of analytics, reporting, and data mining in everyday business environments is imperative to the success of modern businesses. Utilizing Big Data Paradigms for Business Intelligence is a pivotal reference source that provides vital research on how to address the challenges of data extraction in business intelligence using the five “Vs” of big data: velocity, volume, value, variety, and veracity. This book is ideally designed for business analysts, investors, corporate managers, entrepreneurs, and researchers in the fields of computer science, data science, and business intelligence.

Download or read book Data Mining Foundations and Intelligent Paradigms written by Dawn E. Holmes and published by Springer Science & Business Media. This book was released on 2011-11-09 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many invaluable books available on data mining theory and applications. However, in compiling a volume titled “DATA MINING: Foundations and Intelligent Paradigms: Volume 2: Core Topics including Statistical, Time-Series and Bayesian Analysis” we wish to introduce some of the latest developments to a broad audience of both specialists and non-specialists in this field.

Download or read book Statistical Inference as Severe Testing written by Deborah G. Mayo and published by Cambridge University Press. This book was released on 2018-09-20 with total page 503 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.

Download or read book Machine Learning and Big Data Analytics Paradigms Analysis Applications and Challenges written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-12-14 with total page 648 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended to present the state of the art in research on machine learning and big data analytics. The accepted chapters covered many themes including artificial intelligence and data mining applications, machine learning and applications, deep learning technology for big data analytics, and modeling, simulation, and security with big data. It is a valuable resource for researchers in the area of big data analytics and its applications.

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.

Download or read book Machine Learning Paradigms written by Dionisios N. Sotiropoulos and published by Springer. This book was released on 2016-10-26 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The topic of this monograph falls within the, so-called, biologically motivated computing paradigm, in which biology provides the source of models and inspiration towards the development of computational intelligence and machine learning systems. Specifically, artificial immune systems are presented as a valid metaphor towards the creation of abstract and high level representations of biological components or functions that lay the foundations for an alternative machine learning paradigm. Therefore, focus is given on addressing the primary problems of Pattern Recognition by developing Artificial Immune System-based machine learning algorithms for the problems of Clustering, Classification and One-Class Classification. Pattern Classification, in particular, is studied within the context of the Class Imbalance Problem. The main source of inspiration stems from the fact that the Adaptive Immune System constitutes one of the most sophisticated biological systems that is exceptionally evolved in order to continuously address an extremely unbalanced pattern classification problem, namely, the self / non-self discrimination process. The experimental results presented in this monograph involve a wide range of degenerate binary classification problems where the minority class of interest is to be recognized against the vast volume of the majority class of negative patterns. In this context, Artificial Immune Systems are utilized for the development of personalized software as the core mechanism behind the implementation of Recommender Systems. The book will be useful to researchers, practitioners and graduate students dealing with Pattern Recognition and Machine Learning and their applications in Personalized Software and Recommender Systems. It is intended for both the expert/researcher in these fields, as well as for the general reader in the field of Computational Intelligence and, more generally, Computer Science who wishes to learn more about the field of Intelligent Computing Systems and its applications. An extensive list of bibliographic references at the end of each chapter guides the reader to probe further into application area of interest to him/her.

Download or read book Machine Learning Paradigms written by George A. Tsihrintzis and published by Springer. This book was released on 2019-07-06 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is the inaugural volume in the new Springer series on Learning and Analytics in Intelligent Systems. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intelligent systems and related technologies. These disciplines are strongly related and mutually complementary; accordingly, the new series encourages an integrated approach to themes and topics in these disciplines, which will result in significant cross-fertilization, research advances and new knowledge creation. To maximize the dissemination of research findings, the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most.

Download or read book Machine Learning Paradigms written by Aristomenis S. Lampropoulos and published by Springer. This book was released on 2015-06-13 with total page 135 pages. Available in PDF, EPUB and Kindle. Book excerpt: This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and Recommender Systems, as well as for the general reader in the fields of Applied and Computer Science who wishes to learn more about the emerging discipline of Recommender Systems and their applications. Finally, the book provides an extended list of bibliographic references which covers the relevant literature completely.

Download or read book New Learning Paradigms in Soft Computing written by Lakhmi C. Jain and published by Physica. This book was released on 2013-06-05 with total page 477 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.

Download or read book Handbook on Soft Computing for Video Surveillance written by Sankar K. Pal and published by CRC Press. This book was released on 2012-01-25 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information on integrating soft computing techniques into video surveillance is widely scattered among conference papers, journal articles, and books. Bringing this research together in one source, Handbook on Soft Computing for Video Surveillance illustrates the application of soft computing techniques to different tasks in video surveillance. Worldwide experts in the field present novel solutions to video surveillance problems and discuss future trends. After an introduction to video surveillance systems and soft computing tools, the book gives examples of neural network-based approaches for solving video surveillance tasks and describes summarization techniques for content identification. Covering a broad spectrum of video surveillance topics, the remaining chapters explain how soft computing techniques are used to detect moving objects, track objects, and classify and recognize target objects. The book also explores advanced surveillance systems under development. Incorporating both existing and new ideas, this handbook unifies the basic concepts, theories, algorithms, and applications of soft computing. It demonstrates why and how soft computing methodologies can be used in various video surveillance problems.

Download or read book Church Planting in Post Christian Soil written by Christopher James and published by Oxford University Press. This book was released on 2017-11-10 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: National headlines regularly herald the decline of Christianity in the United States, citing historically low levels of confidence in organized religion, drops in church attendance, church closures, and the dramatic rise of the "Nones." Scarcely heard are stories from the thousands of new churches and new forms of church that are springing up each year across the country. In this book, Christopher James attends carefully to stories of ecclesial innovation taking place in Seattle, Washington-a city on the leading edge of trends shaping the nation as a whole. James's study of the new churches founded in this "post-Christian" city offers both theological reflection and pragmatic advice. After an in-depth survey- and -interview-based analysis of the different models of church-planting he encountered, James identifies five threads of practical wisdom: 1) embracing local identity and mission, 2) cultivating embodied, experiential, everyday spirituality, 3) engaging community life as means of witness and formation, 4) prioritizing hospitality as a cornerstone practice, and 5) discovering ecclesial vitality in a diverse ecclesial ecology. Stimulating, encouraging, and stereotype-shattering, this book invites readers to reconsider the narrative that portrays these first decades of the twenty-first century as a period of ecclesial death and decline, and to view our time instead as a hope-filled season of ecclesial renewal and rebirth.