Download or read book On Minimax Parameter Estimation with Loss Functions That Exhibit a Product Structure written by David John Stelte and published by . This book was released on 1973 with total page 65 pages. Available in PDF, EPUB and Kindle. Book excerpt: The report treats minimax parameter estimation problems. Chapters 1 and 2 contain introductory material. Chapter 3 deals with several parameter estimation problems.
Download or read book On Mimimax Parameter Estimation with Loss Functions that Exhibit a Product Structure written by David John Stelte and published by . This book was released on 1973 with total page 110 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Masters Theses in the Pure and Applied Sciences written by Wade H. Shafer and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: Masters Theses in the Pure and Applied Sciences was first conceived, published, and disseminated by TPRC at Purdue University in 1957, starting its coverage of theses with the academic year 1955. Beginning with Volume 13, the printing and dissemina tion phases of the activity was transferred to University Microfilms/Xerox of Ann Arbor, Michigan, with the thought that such an arrangement would be more beneficial to the academic and general scientific and technical community. After five years of this joint undertaking we have concluded that it will be in the interest of all concerned if the printing and distribution of the volume were handled by a well-known publishing house to assure improved service and better communication. Hence, effective with this Volume 18, Masters Theses in the Pure and Applied Sciences will be disseminated on a worldwide basis by Plenum Publishing Corporation of New York. All back issues can also be ordered from Plenum. As we embark on this new partnership with Plenum, we also initiate a new venture in that this important annual reference work now covers Canadian universities as well as those in the United States. We are sure that this broader base will greatly enhance the value of these volumes.
Download or read book Government Reports Announcements written by and published by . This book was released on 1975 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimax Estimation of the Parameter of the Maxwell Distribution Under Quadratic Loss Function written by Huda Abdullah and published by . This book was released on 2016 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This paper is concerned with the problem of finding the minimax estimators of the parameter of the Maxwell distribution (MW) for quadratic loss functions by applying the theorem of Lehmann [1950]. Through simulation study the performance of this method compared with the classical methods containing the Maximum Likelihood and moment Estimators with respect to Mean squared-errors (MSEs) .We reach to that the Minimax estimator with small positive values of c gives the best results, followed by the Maximum likelihood estimator.
Download or read book Government Reports Announcements Index written by and published by . This book was released on 1979-02 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimax Parameter Estimation Under Generalized Quadratic Loss with a Compact Parameter Space written by Rafael Antonio Padilla Lovera and published by . This book was released on 1974 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Government Reports Index written by and published by . This book was released on 1975 with total page 1074 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Minimax Parameter Estimation Under Generalized Quadratic Loss with a Compact Parameter Space written by Rafael Antonio Padilla Lovera 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 Shrinkage Estimation written by Dominique Fourdrinier and published by Springer. This book was released on 2018-11-27 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a coherent framework for understanding shrinkage estimation in statistics. The term refers to modifying a classical estimator by moving it closer to a target which could be known a priori or arise from a model. The goal is to construct estimators with improved statistical properties. The book focuses primarily on point and loss estimation of the mean vector of multivariate normal and spherically symmetric distributions. Chapter 1 reviews the statistical and decision theoretic terminology and results that will be used throughout the book. Chapter 2 is concerned with estimating the mean vector of a multivariate normal distribution under quadratic loss from a frequentist perspective. In Chapter 3 the authors take a Bayesian view of shrinkage estimation in the normal setting. Chapter 4 introduces the general classes of spherically and elliptically symmetric distributions. Point and loss estimation for these broad classes are studied in subsequent chapters. In particular, Chapter 5 extends many of the results from Chapters 2 and 3 to spherically and elliptically symmetric distributions. Chapter 6 considers the general linear model with spherically symmetric error distributions when a residual vector is available. Chapter 7 then considers the problem of estimating a location vector which is constrained to lie in a convex set. Much of the chapter is devoted to one of two types of constraint sets, balls and polyhedral cones. In Chapter 8 the authors focus on loss estimation and data-dependent evidence reports. Appendices cover a number of technical topics including weakly differentiable functions; examples where Stein’s identity doesn’t hold; Stein’s lemma and Stokes’ theorem for smooth boundaries; harmonic, superharmonic and subharmonic functions; and modified Bessel functions.
Download or read book Government Reports Annual Index written by and published by . This book was released on 1974 with total page 1088 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Proceedings written by and published by . This book was released on 1976 with total page 1186 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1991 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Van Nostrand s Scientific Encyclopedia written by Douglas M. Considine and published by Springer Science & Business Media. This book was released on 2013-12-11 with total page 3529 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advancements in science and engineering have occurred at a surprisingly rapid pace since the release of the seventh edition of this encyclopedia. Large portions of the reference have required comprehensive rewriting and new illustrations. Scores of new topics have been included to create this thoroughly updated eighth edition. The appearance of this new edition in 1994 marks the continuation of a tradition commenced well over a half-century ago in 1938 Van Nostrand's Scientific Encyclopedia, First Edition, was published and welcomed by educators worldwide at a time when what we know today as modern science was just getting underway. The early encyclopedia was well received by students and educators alike during a critical time span when science became established as a major factor in shaping the progress and economy of individual nations and at the global level. A vital need existed for a permanent science reference that could be updated periodically and made conveniently available to audiences that numbered in the millions. The pioneering VNSE met these criteria and continues today as a reliable technical information source for making private and public decisions that present a backdrop of technical alternatives.
Download or read book Bulletin Institute of Mathematical Statistics written by Institute of Mathematical Statistics and published by . This book was released on 1989 with total page 636 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.
