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Author : W.L. Harper,Cliff Hooker
Publisher : Springer Science & Business Media
Page : 334 pages
File Size : 41,6 Mb
Release : 1976
Category : Gardening
ISBN : 9027706174
Proceedings of an International Research Colloquium held at the University of Western Ontario, 10-13 May 1973.
Author : William Leonard Harper,Clifford Alan Hooker
Publisher : Unknown
Page : 128 pages
File Size : 47,7 Mb
Release : 1987
Category : Electronic
ISBN : OCLC:38404020
Author : William Leonard Harper,Clifford Alan Hooker
Publisher : Unknown
Page : 264 pages
File Size : 40,5 Mb
Release : 1976
Category : Mathematical statistics
ISBN : UOM:39015017129928
Author : W.L. Harper,C.A. Hooker
Publisher : Springer
Page : 456 pages
File Size : 54,6 Mb
Release : 1975-12-31
Category : Science
ISBN : 9027706190
In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Bayesian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.
Author : William Leonard Harper,Clifford Alan Hooker
Publisher : Springer
Page : 128 pages
File Size : 50,8 Mb
Release : 1975-12-01
Category : Science
ISBN : 902770614X
Author : William Leonard Harper,Clifford Alan Hooker
Publisher : Unknown
Page : 128 pages
File Size : 49,9 Mb
Release : 1976
Category : Electronic
ISBN : OCLC:873215468
Author : W.L. Harper,C.A. Hooker
Publisher : Springer Science & Business Media
Page : 245 pages
File Size : 53,9 Mb
Release : 2012-12-06
Category : Science
ISBN : 9789401014380
In May of 1973 we organized an international research colloquium on foundations of probability, statistics, and statistical theories of science at the University of Western Ontario. During the past four decades there have been striking formal advances in our understanding of logic, semantics and algebraic structure in probabilistic and statistical theories. These advances, which include the development of the relations between semantics and metamathematics, between logics and algebras and the algebraic-geometrical foundations of statistical theories (especially in the sciences), have led to striking new insights into the formal and conceptual structure of probability and statistical theory and their scientific applications in the form of scientific theory. The foundations of statistics are in a state of profound conflict. Fisher's objections to some aspects of Neyman-Pearson statistics have long been well known. More recently the emergence of Bayesian statistics as a radical alternative to standard views has made the conflict especially acute. In recent years the response of many practising statisticians to the conflict has been an eclectic approach to statistical inference. Many good statisticians have developed a kind of wisdom which enables them to know which problems are most appropriately handled by each of the methods available. The search for principles which would explain why each of the methods works where it does and fails where it does offers a fruitful approach to the controversy over foundations.
Author : William L. Harper,C. A. Hooker
Publisher : Unknown
Page : 128 pages
File Size : 53,6 Mb
Release : 1976
Category : Electronic
ISBN : OCLC:834731832
Author : Anonim
Publisher : Unknown
Page : 0 pages
File Size : 49,7 Mb
Release : 1976
Category : Electronic
ISBN : OCLC:1414868275
Author : William Leonard Harper,Clifford Alan Hooker
Publisher : Unknown
Page : 332 pages
File Size : 47,7 Mb
Release : 1976
Category : Mathematical statistics
ISBN : UOM:39015017320931
Author : Anonim
Publisher : Unknown
Page : 128 pages
File Size : 47,6 Mb
Release : 1976
Category : Electronic
ISBN : OCLC:840718005
Author : George Casella,Roger L. Berger
Publisher : Brooks/Cole
Page : 692 pages
File Size : 44,7 Mb
Release : 2002
Category : Mathematics
ISBN : UOM:39015059098130
Casella and Berger's new edition builds the theoretical statistics from the first principals of probability theory. Thoroughly and completely, the authors start with the basics of probability and then move on to develop the theory of statistical inference using techniques, definitions, and statistical concepts.
Author : Clifford A. Hooker,William Leonard Harper,University of Western Ontario
Publisher : Unknown
Page : 455 pages
File Size : 40,8 Mb
Release : 1976
Category : Electronic
ISBN : OCLC:299683841
Author : Jianqing Fan,Runze Li,Cun-Hui Zhang,Hui Zou
Publisher : CRC Press
Page : 942 pages
File Size : 50,7 Mb
Release : 2020-09-21
Category : Mathematics
ISBN : 9780429527616
Statistical Foundations of Data Science gives a thorough introduction to commonly used statistical models, contemporary statistical machine learning techniques and algorithms, along with their mathematical insights and statistical theories. It aims to serve as a graduate-level textbook and a research monograph on high-dimensional statistics, sparsity and covariance learning, machine learning, and statistical inference. It includes ample exercises that involve both theoretical studies as well as empirical applications. The book begins with an introduction to the stylized features of big data and their impacts on statistical analysis. It then introduces multiple linear regression and expands the techniques of model building via nonparametric regression and kernel tricks. It provides a comprehensive account on sparsity explorations and model selections for multiple regression, generalized linear models, quantile regression, robust regression, hazards regression, among others. High-dimensional inference is also thoroughly addressed and so is feature screening. The book also provides a comprehensive account on high-dimensional covariance estimation, learning latent factors and hidden structures, as well as their applications to statistical estimation, inference, prediction and machine learning problems. It also introduces thoroughly statistical machine learning theory and methods for classification, clustering, and prediction. These include CART, random forests, boosting, support vector machines, clustering algorithms, sparse PCA, and deep learning.
Author : Terrence L. Fine
Publisher : Academic Press
Page : 276 pages
File Size : 45,7 Mb
Release : 2014-05-10
Category : Mathematics
ISBN : 9781483263892
Theories of Probability: An Examination of Foundations reviews the theoretical foundations of probability, with emphasis on concepts that are important for the modeling of random phenomena and the design of information processing systems. Topics covered range from axiomatic comparative and quantitative probability to the role of relative frequency in the measurement of probability. Computational complexity and random sequences are also discussed. Comprised of nine chapters, this book begins with an introduction to different types of probability theories, followed by a detailed account of axiomatic formalizations of comparative and quantitative probability and the relations between them. Subsequent chapters focus on the Kolmogorov formalization of quantitative probability; the common interpretation of probability as a limit of the relative frequency of the number of occurrences of an event in repeated, unlinked trials of a random experiment; an improved theory for repeated random experiments; and the classical theory of probability. The book also examines the origin of subjective probability as a by-product of the development of individual judgments into decisions. Finally, it suggests that none of the known theories of probability covers the whole domain of engineering and scientific practice. This monograph will appeal to students and practitioners in the fields of mathematics and statistics as well as engineering and the physical and social sciences.