Download or read book Proceedings of Conference on Foundational Questions in Statistical Inference written by Conference on Foundational Questions in Statistical Inference and published by . This book was released on 1974 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Foundational Questions in Statistical Inference written by Aarhus universitet. Afdeling for teoretisk statistik and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Foundational Questions in Statistical Inference written by O. Barndorff-Nielsen and published by . This book was released on 1974 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of Conference on Foundational Questions in Statistical Inference Aarhus May 7 12 1973 written by and published by . This book was released on 1974 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of Conference on Foundational Questions in Statistical Inference written by Conference on Foundational Questions in Statistical Inference and published by . This book was released on 1974 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of the Conference on Foundational Questions in Statistical Inference Aaehus May 7 12 1973 written by and published by . This book was released on 1973 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of Conference on Foundational Questions in Statistical Inference Aarhus May 7 l2 1973 written by and published by . This book was released on 1974 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of Conference on Foundational written by Ole Barndorff-Nielsen and published by . This book was released on 1974 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Proceedings of Conference on Foundational Questions in Statistical Inference Aarhus May 7 12 1973 written by and published by . This book was released on 1974 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Aspects of Statistical Inference written by A. H. Welsh and published by John Wiley & Sons. This book was released on 2011-09-15 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: Relevant, concrete, and thorough--the essential data-based text onstatistical inference The ability to formulate abstract concepts and draw conclusionsfrom data is fundamental to mastering statistics. Aspects ofStatistical Inference equips advanced undergraduate and graduatestudents with a comprehensive grounding in statistical inference,including nonstandard topics such as robustness, randomization, andfinite population inference. A. H. Welsh goes beyond the standard texts and expertly synthesizesbroad, critical theory with concrete data and relevant topics. Thetext follows a historical framework, uses real-data sets andstatistical graphics, and treats multiparameter problems, yet isultimately about the concepts themselves. Written with clarity and depth, Aspects of Statistical Inference: * Provides a theoretical and historical grounding in statisticalinference that considers Bayesian, fiducial, likelihood, andfrequentist approaches * Illustrates methods with real-data sets on diabetic retinopathy,the pharmacological effects of caffeine, stellar velocity, andindustrial experiments * Considers multiparameter problems * Develops large sample approximations and shows how to use them * Presents the philosophy and application of robustness theory * Highlights the central role of randomization in statistics * Uses simple proofs to illuminate foundational concepts * Contains an appendix of useful facts concerning expansions,matrices, integrals, and distribution theory Here is the ultimate data-based text for comparing and presentingthe latest approaches to statistical inference.

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 Statistical Inference written by Murray Aitkin and published by CRC Press. This book was released on 2010-06-02 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filling a gap in current Bayesian theory, Statistical Inference: An Integrated Bayesian/Likelihood Approach presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications. This novel approach provides new solutions to difficult model comparison problems and offers direct

Download or read book Transactions of the Eighth Prague Conference written by J. Kozesnik and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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 564 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

Download or read book Introduction to Statistical Modelling and Inference written by Murray Aitkin and published by CRC Press. This book was released on 2022-09-30 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: The complexity of large-scale data sets (“Big Data”) has stimulated the development of advanced computational methods for analysing them. There are two different kinds of methods to aid this. The model-based method uses probability models and likelihood and Bayesian theory, while the model-free method does not require a probability model, likelihood or Bayesian theory. These two approaches are based on different philosophical principles of probability theory, espoused by the famous statisticians Ronald Fisher and Jerzy Neyman. Introduction to Statistical Modelling and Inference covers simple experimental and survey designs, and probability models up to and including generalised linear (regression) models and some extensions of these, including finite mixtures. A wide range of examples from different application fields are also discussed and analysed. No special software is used, beyond that needed for maximum likelihood analysis of generalised linear models. Students are expected to have a basic mathematical background in algebra, coordinate geometry and calculus. Features • Probability models are developed from the shape of the sample empirical cumulative distribution function (cdf) or a transformation of it. • Bounds for the value of the population cumulative distribution function are obtained from the Beta distribution at each point of the empirical cdf. • Bayes’s theorem is developed from the properties of the screening test for a rare condition. • The multinomial distribution provides an always-true model for any randomly sampled data. • The model-free bootstrap method for finding the precision of a sample estimate has a model-based parallel – the Bayesian bootstrap – based on the always-true multinomial distribution. • The Bayesian posterior distributions of model parameters can be obtained from the maximum likelihood analysis of the model. This book is aimed at students in a wide range of disciplines including Data Science. The book is based on the model-based theory, used widely by scientists in many fields, and compares it, in less detail, with the model-free theory, popular in computer science, machine learning and official survey analysis. The development of the model-based theory is accelerated by recent developments in Bayesian analysis.

Download or read book Resampling Methods written by Phillip I. Good and published by Springer Science & Business Media. This book was released on 2013-04-18 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: "...the author has packaged an excellent and modern set of topics around the development and use of quantitative models...the author has the capability to work at a more modest level. He does that very effectively in this 2nd Edition... If you need to learn about resampling, this book would be a good place to start." -- Technometrics This work is a practical, table-free introduction to data analysis using the bootstrap, cross-validation, and permutation tests; new to the second edition are several additional examples and a chapter dedicated to regression, data mining techniques, and their limitations. The book’s many exercises, practical data sets, and use of free shareware make it an essential resource for students and teachers, as well as industrial statisticians, consultants, and research professionals.

Download or read book Selected Works of Debabrata Basu written by Anirban DasGupta and published by Springer Science & Business Media. This book was released on 2011-02-04 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains a little more than 20 of Debabrata Basu's most significant articles and writings. Debabrata Basu is internationally known for his highly influential and fundamental contributions to the foundations of statistics, survey sampling, sufficiency, and invariance. The major theorem bearing his name has had numerous applications to statistics and probability. The articles in this volume are reprints of the original articles, in a chronological order. The book also contains eleven commentaries written by some of the most distinguished scholars in the area of foundations and statistical inference. These commentaries are by George Casella and V. Gopal, Phil Dawid, Tom DiCiccio and Alastair Young, Malay Ghosh, Jay kadane, Glen Meeden, Robert Serfling, Jayaram Sethuraman, Terry Speed, and Alan Welsh.