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A Natural Identity For Exponential Families With Applications In Multiparameter Estimation
Download A Natural Identity For Exponential Families With Applications In Multiparameter Estimation full books in PDF, epub, and Kindle. Read online A Natural Identity For Exponential Families With Applications In Multiparameter Estimation ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis A Natural Identity for Exponential Families with Applications in Multiparameter Estimation by : H. Malcolm Hudson
Download or read book A Natural Identity for Exponential Families with Applications in Multiparameter Estimation written by H. Malcolm Hudson and published by . This book was released on 1977 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Fundamentals of Statistical Exponential Families by : Lawrence D. Brown
Download or read book Fundamentals of Statistical Exponential Families written by Lawrence D. Brown and published by IMS. This book was released on 1986 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Stein's Method written by Persi Diaconis and published by IMS. This book was released on 2004 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: "These papers were presented and developed as expository talks at a summer-long workshop on Stein's method at Stanford's Department of Statistics in 1998."--P. iii.
Book Synopsis Selected Works of Peter J. Bickel by : Jianqing Fan
Download or read book Selected Works of Peter J. Bickel written by Jianqing Fan and published by Springer Science & Business Media. This book was released on 2012-11-28 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents selections of Peter J. Bickel’s major papers, along with comments on their novelty and impact on the subsequent development of statistics as a discipline. Each of the eight parts concerns a particular area of research and provides new commentary by experts in the area. The parts range from Rank-Based Nonparametrics to Function Estimation and Bootstrap Resampling. Peter’s amazing career encompasses the majority of statistical developments in the last half-century or about about half of the entire history of the systematic development of statistics. This volume shares insights on these exciting statistical developments with future generations of statisticians. The compilation of supporting material about Peter’s life and work help readers understand the environment under which his research was conducted. The material will also inspire readers in their own research-based pursuits. This volume includes new photos of Peter Bickel, his biography, publication list, and a list of his students. These give the reader a more complete picture of Peter Bickel as a teacher, a friend, a colleague, and a family man.
Book Synopsis Rethinking Biased Estimation by : Yonina C. Eldar
Download or read book Rethinking Biased Estimation written by Yonina C. Eldar and published by Now Publishers Inc. This book was released on 2008 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rethinking Biased Estimation discusses methods to improve the accuracy of unbiased estimators used in many signal processing problems. At the heart of the proposed methodology is the use of the mean-squared error (MSE) as the performance criteria. One of the prime goals of statistical estimation theory is the development of performance bounds when estimating parameters of interest in a given model, as well as constructing estimators that achieve these limits. When the parameters to be estimated are deterministic, a popular approach is to bound the MSE achievable within the class of unbiased estimators. Although it is well-known that lower MSE can be obtained by allowing for a bias, in applications it is typically unclear how to choose an appropriate bias. Rethinking Biased Estimation introduces MSE bounds that are lower than the unbiased Cramer-Rao bound (CRB) for all values of the unknowns. It then presents a general framework for constructing biased estimators with smaller MSE than the standard maximum-likelihood (ML) approach, regardless of the true unknown values. Specializing the results to the linear Gaussian model, it derives a class of estimators that dominate least-squares in terms of MSE. It also introduces methods for choosing regularization parameters in penalized ML estimators that outperform standard techniques such as cross validation.
Book Synopsis Bayesian Methods by : Thomas Leonard
Download or read book Bayesian Methods written by Thomas Leonard and published by Cambridge University Press. This book was released on 2001-08-06 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian statistics directed towards mainstream statistics. How to infer scientific, medical, and social conclusions from numerical data.
Book Synopsis Probability and Statistical Models with Applications by : CH. A. Charalambides
Download or read book Probability and Statistical Models with Applications written by CH. A. Charalambides and published by CRC Press. This book was released on 2000-09-21 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph of carefully collected articles reviews recent developments in theoretical and applied statistical science, highlights current noteworthy results and illustrates their applications; and points out possible new directions to pursue. With its enlightening account of statistical discoveries and its numerous figures and tables, Probabili
Book Synopsis Inference and Learning from Data by : Ali H. Sayed
Download or read book Inference and Learning from Data written by Ali H. Sayed and published by Cambridge University Press. This book was released on 2022-11-30 with total page 1105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover core topics in inference and learning with the first volume of this extraordinary three-volume set.
Book Synopsis Statistical Inference by : George Casella
Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.
Book Synopsis Shrinkage Estimation by : Dominique Fourdrinier
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.
Book Synopsis Statistical Decision Theory and Related Topics III by : Shanti S. Gupta
Download or read book Statistical Decision Theory and Related Topics III written by Shanti S. Gupta and published by Academic Press. This book was released on 2014-05-10 with total page 551 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Decision Theory and Related Topics III, Volume 2 is a collection of papers presented at the Third Purdue Symposium on Statistical Decision Theory and Related Topics, held at Purdue University in June 1981. The symposium brought together many prominent leaders and a number of younger researchers in statistical decision theory and related areas. This volume contains the research papers presented at the symposium and includes works on general decision theory, multiple decision theory, optimum experimental design, sequential and adaptive inference, Bayesian analysis, robustness, and large sample theory. These research areas have seen rapid developments since the preceding Purdue Symposium in 1976, developments reflected by the variety and depth of the works in this volume. Statisticians and mathematicians will find the book very insightful.
Book Synopsis Theory of Point Estimation by : Erich L. Lehmann
Download or read book Theory of Point Estimation written by Erich L. Lehmann and published by Springer Science & Business Media. This book was released on 2006-05-02 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second, much enlarged edition by Lehmann and Casella of Lehmann's classic text on point estimation maintains the outlook and general style of the first edition. All of the topics are updated, while an entirely new chapter on Bayesian and hierarchical Bayesian approaches is provided, and there is much new material on simultaneous estimation. Each chapter concludes with a Notes section which contains suggestions for further study. This is a companion volume to the second edition of Lehmann's "Testing Statistical Hypotheses".
Book Synopsis Sampling Theory, a Renaissance by : Götz E. Pfander
Download or read book Sampling Theory, a Renaissance written by Götz E. Pfander and published by Birkhäuser. This book was released on 2015-12-08 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reconstructing or approximating objects from seemingly incomplete information is a frequent challenge in mathematics, science, and engineering. A multitude of tools designed to recover hidden information are based on Shannon’s classical sampling theorem, a central pillar of Sampling Theory. The growing need to efficiently obtain precise and tailored digital representations of complex objects and phenomena requires the maturation of available tools in Sampling Theory as well as the development of complementary, novel mathematical theories. Today, research themes such as Compressed Sensing and Frame Theory re-energize the broad area of Sampling Theory. This volume illustrates the renaissance that the area of Sampling Theory is currently experiencing. It touches upon trendsetting areas such as Compressed Sensing, Finite Frames, Parametric Partial Differential Equations, Quantization, Finite Rate of Innovation, System Theory, as well as sampling in Geometry and Algebraic Topology.
Book Synopsis Technical Report by : University of Wisconsin--Madison. Department of Statistics
Download or read book Technical Report written by University of Wisconsin--Madison. Department of Statistics and published by . This book was released on 1972 with total page 476 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Journal of Statistical Planning and Inference by : North-Holland Publishing Company
Download or read book Journal of Statistical Planning and Inference written by North-Holland Publishing Company and published by . This book was released on 1997 with total page 1216 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Discrete Wavelet Transforms by : Juuso T. Olkkonen
Download or read book Discrete Wavelet Transforms written by Juuso T. Olkkonen and published by BoD – Books on Demand. This book was released on 2011-04-04 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete wavelet transform (DWT) algorithms have become standard tools for discrete-time signal and image processing in several areas in research and industry. As DWT provides both frequency and location information of the analyzed signal, it is constantly used to solve and treat more and more advanced problems. The present book: Discrete Wavelet Transforms: Theory and Applications describes the latest progress in DWT analysis in non-stationary signal processing, multi-scale image enhancement as well as in biomedical and industrial applications. Each book chapter is a separate entity providing examples both the theory and applications. The book comprises of tutorial and advanced material. It is intended to be a reference text for graduate students and researchers to obtain in-depth knowledge in specific applications.
Book Synopsis Recent Advances in Statistics by : M. Haseeb Rizvi
Download or read book Recent Advances in Statistics written by M. Haseeb Rizvi and published by Academic Press. This book was released on 2014-05-10 with total page 626 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent Advances in Statistics: Papers in Honor of Herman Chernoff on His Sixtieth Birthday is a collection of papers on statistics in honor of Herman Chernoff on the occasion of his 60th birthday. Topics covered range from sequential analysis (including designs) to optimization (including control theory), nonparametrics (including large sample theory), and statistical graphics. Comprised of 27 chapters, this book begins with a discussion on optimal stopping of Brownian motion, followed by an analysis of sequential design of comparative clinical trials. A two-sample sequential test for shift with one sample size fixed in advance is then presented. Subsequent chapters focus on set-valued parameters and set-valued statistics; large deviations of the maximum likelihood estimate in the Markov chain case; the limiting behavior of multiple roots of the likelihood equation; and optimal uniform rate of convergence for nonparametric estimators of a density function and its derivatives. The book concludes by considering significance and confidence levels, closed regions and models, and discrete distributions. This monograph should be of interest to students, researchers, and specialists in the fields of mathematics and statistics.
