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Kendalls Advanced Theory Of Statistics Classical Inference And The Linear Model
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Book Synopsis Kendall's Advanced Theory of Statistics, Classical Inference and the Linear Model by : Alan Stuart
Download or read book Kendall's Advanced Theory of Statistics, Classical Inference and the Linear Model written by Alan Stuart and published by Wiley. This book was released on 2010-02-22 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of statistical theory in the past fifty years is faithfully reflected in the history of the late Sir Maurice Kendall’s volumes The Advanced Theory of Statistics. The Advanced Theory began life as a two volume work (Volume 1, 1943; Volume 2, 1946) and grew steadily, as a single authored work until the late fifties. At that point Alan Stuart became involved and the Advanced Theory was rewritten in three volumes. When Keith Ord joined in the early eighties, Volume 3 became the largest and plans were developed to expand it into a series of monographs called the Kendall's Library of Statistics which would devote a book to each of the modern developments in statistics. This series is well on the way with 5 titles in print and a further 7 on the way. A new volume on Bayesian Inference was also commissioned from Tony O'Hagan and published in 1994 as Volume 2B of the Advanced Theory. This Volume 2A is therefore the completely updated Volume 2 - Classical Inference and Relationship. A new author, Steven Arnold, was invited to join Keith Ord and they have between them produced a work of the highest quality. References have been updated and material revised throughout. A new chapter on the linear model and least squares estimation has been added.
Book Synopsis Kendall's Advanced Theory of Statistics, Classical Inference and the Linear Model by : Alan Stuart
Download or read book Kendall's Advanced Theory of Statistics, Classical Inference and the Linear Model written by Alan Stuart and published by Wiley. This book was released on 2009-01-27 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt: The development of statistical theory in the past fifty years is faithfully reflected in the history of the late Sir Maurice Kendall’s volumes The Advanced Theory of Statistics. The Advanced Theory began life as a two volume work (Volume 1, 1943; Volume 2, 1946) and grew steadily, as a single authored work until the late fifties. At that point Alan Stuart became involved and the Advanced Theory was rewritten in three volumes. When Keith Ord joined in the early eighties, Volume 3 became the largest and plans were developed to expand it into a series of monographs called the Kendall's Library of Statistics which would devote a book to each of the modern developments in statistics. This series is well on the way with 5 titles in print and a further 7 on the way. A new volume on Bayesian Inference was also commissioned from Tony O'Hagan and published in 1994 as Volume 2B of the Advanced Theory. This Volume 2A is therefore the completely updated Volume 2 - Classical Inference and Relationship. A new author, Steven Arnold, was invited to join Keith Ord and they have between them produced a work of the highest quality. References have been updated and material revised throughout. A new chapter on the linear model and least squares estimation has been added.
Book Synopsis Kendall's Advanced Theory of Statistics, Distribution Theory by : Maurice George Kendall
Download or read book Kendall's Advanced Theory of Statistics, Distribution Theory written by Maurice George Kendall and published by Wiley-Interscience. This book was released on 1994-06-30 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: This major revision contains a largely new chapter 7 providing an extensive discussion of the bivariate and multivariate versions of the standard distributions and families. Chapter 16 has been enlarged to cover multivariate sampling theory, an updated version of material previously found inthe old Volume III. The previous chapters 7 and 8 have been condensed into a single chapter providing an introduction to statistical inference. Elsewhere, major updates include new material on skewness and kurtosis, hazard rate distributions, the bootstrap, the evaluation of the multivariate normalintegral and ratios of quadratic forms. The new edition includes over 200 new references, 40 new exercises and 20 further examples in the main text. In addition, all the text examples have been given titles, and these are listed at the front of the book for easier reference.
Book Synopsis Kendalls Advanced Theory of Statistics, 3 Volume Set by : Alan Stuart
Download or read book Kendalls Advanced Theory of Statistics, 3 Volume Set written by Alan Stuart and published by Wiley. This book was released on 2009-02-24 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This 3-volume set offers the complete, classic Kendall's Advanced Theory of Statistics in a single, value-for-money pack. The latest set includes the brand new second edition of the popular 'Volume 2B: Bayesian Inference', along with the sixth editions of 'Volume 1: Distribution Theory' and 'Volume 2A: Classical Inference and the Linear Model'.
Book Synopsis Kendall's Advanced Theory of Statistic 2B by : Anthony O'Hagan
Download or read book Kendall's Advanced Theory of Statistic 2B written by Anthony O'Hagan and published by John Wiley & Sons. This book was released on 2010-03-08 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kendall's Advanced Theory of Statistics and Kendall's Library of Statistics The development of modern statistical theory in the past fifty years is reflected in the history of the late Sir Maurice Kenfall's volumes The Advanced Theory of Statistics. The Advanced Theory began life as a two-volume work, and since its first appearance in 1943, has been an indispensable source for the core theory of classical statistics. With Bayesian Inference, the same high standard has been applied to this important and exciting new body of theory.
Book Synopsis Kendall's Advanced Theory of Statistics Volume 2 5ed Classical Inference and Relationship by : Alan Stuart
Download or read book Kendall's Advanced Theory of Statistics Volume 2 5ed Classical Inference and Relationship written by Alan Stuart and published by . This book was released on 1991-06-06 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kendall's Advanced Theory of Statistics, Distribution Theory by : Alan Stuart
Download or read book Kendall's Advanced Theory of Statistics, Distribution Theory written by Alan Stuart and published by John Wiley & Sons. This book was released on 2010-02-22 with total page 709 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kendall's Advanced Theory of Statistics and Kendall's Library of Statistics The development of modern statistical theory is reflected in the history of the late Sir Maurice Kenfall's volumes, The Advanced Theory of Statistics. This landmark publication began life as a two-volume work and grew steadily as a single-authored work until the 1950s. In this edition, there is new material on skewness and kurtosis, hazard rate distribution, the bootstrap, the evaluation of the multivariate normal integral and ratios of quadratic forms. It also includes over 200 new references, 40 new exercises, and 20 further examples in the main text.
Book Synopsis Linear Models and Time-Series Analysis by : Marc S. Paolella
Download or read book Linear Models and Time-Series Analysis written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-12-17 with total page 896 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and timely edition on an emerging new trend in time series Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH sets a strong foundation, in terms of distribution theory, for the linear model (regression and ANOVA), univariate time series analysis (ARMAX and GARCH), and some multivariate models associated primarily with modeling financial asset returns (copula-based structures and the discrete mixed normal and Laplace). It builds on the author's previous book, Fundamental Statistical Inference: A Computational Approach, which introduced the major concepts of statistical inference. Attention is explicitly paid to application and numeric computation, with examples of Matlab code throughout. The code offers a framework for discussion and illustration of numerics, and shows the mapping from theory to computation. The topic of time series analysis is on firm footing, with numerous textbooks and research journals dedicated to it. With respect to the subject/technology, many chapters in Linear Models and Time-Series Analysis cover firmly entrenched topics (regression and ARMA). Several others are dedicated to very modern methods, as used in empirical finance, asset pricing, risk management, and portfolio optimization, in order to address the severe change in performance of many pension funds, and changes in how fund managers work. Covers traditional time series analysis with new guidelines Provides access to cutting edge topics that are at the forefront of financial econometrics and industry Includes latest developments and topics such as financial returns data, notably also in a multivariate context Written by a leading expert in time series analysis Extensively classroom tested Includes a tutorial on SAS Supplemented with a companion website containing numerous Matlab programs Solutions to most exercises are provided in the book Linear Models and Time-Series Analysis: Regression, ANOVA, ARMA and GARCH is suitable for advanced masters students in statistics and quantitative finance, as well as doctoral students in economics and finance. It is also useful for quantitative financial practitioners in large financial institutions and smaller finance outlets.
Book Synopsis Twelve British Statisticians by : Richard H. Williams
Download or read book Twelve British Statisticians written by Richard H. Williams and published by Bitingduck Press LLC. This book was released on 2006 with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt: Twelve British Statisticians provides a description of the lives and contributions of a dozen scientific luminaries. Their fields of expertise sometimes include disciplines that depart from statistics and display great versatility. Each statistician is a famous figure, but is especially renowned in Great Britain. The book is accessible to a wide reading audience. Each chapter focuses on the scientific contributions and personal life of a single statistician. Each chapter begins with an overview and contains a rich set of references. Current textbooks in statistics contain little information about the pioneers in the field. This book provides a historical supplement in courses on quantitative methods in the behavioral, social, and biological disciplines. The statisticians and some of their contributions covered include: 1. Karl Pearson: product-moment correlation. 2. R.A. Fisher: analysis of variance and covariance, experimental design, common sampling distributions. 3. Charles Spearman: factor analysis, theory of intelligence, mental test theory. 4. Florence Nightingale David: advocate of womenOCOs vocational rights in statistics, distinguished educator. 5. George Udny Yule: time series, contingency table analysis. 6. Maurice G. Kendall: generation of and tests for randomness, time series. 7. George E.P. Box: statistical quality control, analysis of time series. 8. William Sealy Gosset (OC StudentOCO): small sample statistical techniques, contributions to Neyman-Pearson theory. 9. Egon Sharpe Pearson: Neyman-Pearson theory, history of statistics. 10. Francis Ysidro Edgeworth: polymath mathematical psychics, editor of the Economics Journal . 11. Maurice S. Bartlett: stochastic processes, epidemiology, time series. 12. David Cox: multivariable models including covariates and treatment variables, survival rate. For author bios, photos, and a sample read, visit www.bosonbooks.com"
Book Synopsis The SAGE Encyclopedia of Social Science Research Methods by : Michael Lewis-Beck
Download or read book The SAGE Encyclopedia of Social Science Research Methods written by Michael Lewis-Beck and published by SAGE. This book was released on 2004 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring over 900 entries, this resource covers all disciplines within the social sciences with both concise definitions & in-depth essays.
Book Synopsis Classic Topics on the History of Modern Mathematical Statistics by : Prakash Gorroochurn
Download or read book Classic Topics on the History of Modern Mathematical Statistics written by Prakash Gorroochurn and published by John Wiley & Sons. This book was released on 2016-04-04 with total page 776 pages. Available in PDF, EPUB and Kindle. Book excerpt: "There is nothing like it on the market...no others are as encyclopedic...the writing is exemplary: simple, direct, and competent." —George W. Cobb, Professor Emeritus of Mathematics and Statistics, Mount Holyoke College Written in a direct and clear manner, Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times presents a comprehensive guide to the history of mathematical statistics and details the major results and crucial developments over a 200-year period. Presented in chronological order, the book features an account of the classical and modern works that are essential to understanding the applications of mathematical statistics. Divided into three parts, the book begins with extensive coverage of the probabilistic works of Laplace, who laid much of the foundations of later developments in statistical theory. Subsequently, the second part introduces 20th century statistical developments including work from Karl Pearson, Student, Fisher, and Neyman. Lastly, the author addresses post-Fisherian developments. Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times also features: A detailed account of Galton's discovery of regression and correlation as well as the subsequent development of Karl Pearson's X2 and Student's t A comprehensive treatment of the permeating influence of Fisher in all aspects of modern statistics beginning with his work in 1912 Significant coverage of Neyman–Pearson theory, which includes a discussion of the differences to Fisher’s works Discussions on key historical developments as well as the various disagreements, contrasting information, and alternative theories in the history of modern mathematical statistics in an effort to provide a thorough historical treatment Classic Topics on the History of Modern Mathematical Statistics: From Laplace to More Recent Times is an excellent reference for academicians with a mathematical background who are teaching or studying the history or philosophical controversies of mathematics and statistics. The book is also a useful guide for readers with a general interest in statistical inference.
Book Synopsis Handbook of Bayesian, Fiducial, and Frequentist Inference by : James Berger
Download or read book Handbook of Bayesian, Fiducial, and Frequentist Inference written by James Berger and published by CRC Press. This book was released on 2024-02-26 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: The emergence of data science, in recent decades, has magnified the need for efficient methodology for analyzing data and highlighted the importance of statistical inference. Despite the tremendous progress that has been made, statistical science is still a young discipline and continues to have several different and competing paths in its approaches and its foundations. While the emergence of competing approaches is a natural progression of any scientific discipline, differences in the foundations of statistical inference can sometimes lead to different interpretations and conclusions from the same dataset. The increased interest in the foundations of statistical inference has led to many publications, and recent vibrant research activities in statistics, applied mathematics, philosophy and other fields of science reflect the importance of this development. The BFF approaches not only bridge foundations and scientific learning, but also facilitate objective and replicable scientific research, and provide scalable computing methodologies for the analysis of big data. Most of the published work typically focusses on a single topic or theme, and the body of work is scattered in different journals. This handbook provides a comprehensive introduction and broad overview of the key developments in the BFF schools of inference. It is intended for researchers and students who wish for an overview of foundations of inference from the BFF perspective and provides a general reference for BFF inference. Key Features: Provides a comprehensive introduction to the key developments in the BFF schools of inference Gives an overview of modern inferential methods, allowing scientists in other fields to expand their knowledge Is accessible for readers with different perspectives and backgrounds
Book Synopsis Fundamental Statistical Inference by : Marc S. Paolella
Download or read book Fundamental Statistical Inference written by Marc S. Paolella and published by John Wiley & Sons. This book was released on 2018-09-04 with total page 582 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on approach to statistical inference that addresses the latest developments in this ever-growing field This clear and accessible book for beginning graduate students offers a practical and detailed approach to the field of statistical inference, providing complete derivations of results, discussions, and MATLAB programs for computation. It emphasizes details of the relevance of the material, intuition, and discussions with a view towards very modern statistical inference. In addition to classic subjects associated with mathematical statistics, topics include an intuitive presentation of the (single and double) bootstrap for confidence interval calculations, shrinkage estimation, tail (maximal moment) estimation, and a variety of methods of point estimation besides maximum likelihood, including use of characteristic functions, and indirect inference. Practical examples of all methods are given. Estimation issues associated with the discrete mixtures of normal distribution, and their solutions, are developed in detail. Much emphasis throughout is on non-Gaussian distributions, including details on working with the stable Paretian distribution and fast calculation of the noncentral Student's t. An entire chapter is dedicated to optimization, including development of Hessian-based methods, as well as heuristic/genetic algorithms that do not require continuity, with MATLAB codes provided. The book includes both theory and nontechnical discussions, along with a substantial reference to the literature, with an emphasis on alternative, more modern approaches. The recent literature on the misuse of hypothesis testing and p-values for model selection is discussed, and emphasis is given to alternative model selection methods, though hypothesis testing of distributional assumptions is covered in detail, notably for the normal distribution. Presented in three parts—Essential Concepts in Statistics; Further Fundamental Concepts in Statistics; and Additional Topics—Fundamental Statistical Inference: A Computational Approach offers comprehensive chapters on: Introducing Point and Interval Estimation; Goodness of Fit and Hypothesis Testing; Likelihood; Numerical Optimization; Methods of Point Estimation; Q-Q Plots and Distribution Testing; Unbiased Point Estimation and Bias Reduction; Analytic Interval Estimation; Inference in a Heavy-Tailed Context; The Method of Indirect Inference; and, as an appendix, A Review of Fundamental Concepts in Probability Theory, the latter to keep the book self-contained, and giving material on some advanced subjects such as saddlepoint approximations, expected shortfall in finance, calculation with the stable Paretian distribution, and convergence theorems and proofs.
Book Synopsis The advanced theory of statistics. 2 by : Maurice G. Kendall
Download or read book The advanced theory of statistics. 2 written by Maurice G. Kendall and published by . This book was released on 1955 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimation; Confidence intervals; Fiducial inference; Some common tests of significance; Regression; The analysis of variance; The design of sampling inquiries; Multivariate analysis.
Book Synopsis The Advanced Theory of Statistics: Inference and relationship by : Maurice George Kendall
Download or read book The Advanced Theory of Statistics: Inference and relationship written by Maurice George Kendall and published by . This book was released on 1973 with total page 744 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data Science written by Ivo D. Dinov and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-12-06 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
Book Synopsis Estimation and Inferential Statistics by : Pradip Kumar Sahu
Download or read book Estimation and Inferential Statistics written by Pradip Kumar Sahu and published by Springer. This book was released on 2015-11-03 with total page 317 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the meaning of statistical inference and estimation. Statistical inference is concerned with the problems of estimation of population parameters and testing hypotheses. Primarily aimed at undergraduate and postgraduate students of statistics, the book is also useful to professionals and researchers in statistical, medical, social and other disciplines. It discusses current methodological techniques used in statistics and related interdisciplinary areas. Every concept is supported with relevant research examples to help readers to find the most suitable application. Statistical tools have been presented by using real-life examples, removing the “fear factor” usually associated with this complex subject. The book will help readers to discover diverse perspectives of statistical theory followed by relevant worked-out examples. Keeping in mind the needs of readers, as well as constantly changing scenarios, the material is presented in an easy-to-understand form.
