Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
On Limits Of Uniquely Best Linear Estimators
Download On Limits Of Uniquely Best Linear Estimators full books in PDF, epub, and Kindle. Read online On Limits Of Uniquely Best Linear Estimators ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis On Limits of Uniquely Best Linear Estimators by : Lynn Roy LaMotte
Download or read book On Limits of Uniquely Best Linear Estimators written by Lynn Roy LaMotte and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: In a general linear model, it is shown that all admissible linear estimators are limits of linear estimators that are uniquely best at some point in an extended parameter set. The principal result shows that a linear estimator that is uniquely best at a point W2 among multiple linear estimators that are best at a point W1 is the limit of uniquely best estimators at points approaching W1 along the line joining W1 and W2.
Book Synopsis Restricted Parameter Space Estimation Problems by : Constance van Eeden
Download or read book Restricted Parameter Space Estimation Problems written by Constance van Eeden and published by Springer Science & Business Media. This book was released on 2006-12-15 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph is addressed to anyone interested in the subject of restrict- parameter-space estimation, and in particular to those who want to learn, or bring their knowledge up to date, about (in)admissibility and minimaxity problems for such parameter spaces. The coverage starts in the early 1950s when the subject of inference for - stricted parameter spaces began to be studied and ends around the middle of 2004. It presents known, and also some new, results on (in)admissibility and minimaxity for nonsequential point estimation problems in restricted ?ni- dimensional parameter spaces. Relationships between various results are d- cussed and open problems are pointed out. Few complete proofs are given, but outlines of proofs are often supplied. The reader is always referred to the published papers and often results are clari?ed by presenting examples of the kind of problems an author solves, or of problems that cannot be solved by a particular result. The monograph does not touch on the subject of testing hypotheses in - stricted parameter spaces. The latest books on that subject are by Robertson, Wright and Dykstra (1988) and Akkerboom (1990), but many new results in that area have been obtained since. The monograph does have a chapter in which questions about the existence of maximum likelihood estimators are discussed. Some of their properties are also given there as well as some algorithms for computing them. Most of these results cannot be found in the Robertson, Wright, Dykstra book.
Book Synopsis Probability and Mathematical Statistics by :
Download or read book Probability and Mathematical Statistics written by and published by . This book was released on 1989 with total page 676 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Mathematical Reviews written by and published by . This book was released on 1999 with total page 1244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Admissible Linear Estimators in Mixed Linear Models by : Czesław Stepniak
Download or read book Admissible Linear Estimators in Mixed Linear Models written by Czesław Stepniak and published by . This book was released on 1988 with total page 48 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Selected Papers of C.R. Rao by : Calyampudi Radhakrishna Rao
Download or read book Selected Papers of C.R. Rao written by Calyampudi Radhakrishna Rao and published by Taylor & Francis. This book was released on 1989 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Is The Fourth Volume Of Selected Papers Of C. R. Rao Consisting Of 39 Papers Published During 1975-1985. These Papers Represent The Development Of Some Of The Basic Concepts Proposed By The Author In The Fields Of Unified Theory Of Least Squares Estimation, Weighted Distributions, Bayesian Statistical Inference, Generalised Inverses Of Matrices And Their Applications In Which Contemporary Research Is Carried Out Extensively. Work On Solutions Of Functional Equations And Their Application In Characterizations Of Distributions Is Also Of Current Interest. Introduction Of Measures Of Diversity, Quadratic Entropy And Allied Concepts Find Applications In Various Fields Such As Anthropology And Social Sciences. As In The Earlier Volumes, The Papers That Have Originally Appeared In Different Publications Have Been Retypeset To Maintain Uniformity In Presentation.The Final Volume With More Papers, An Updated Bibliography Of Works And A Comprehensive Overview Of The Total Opus Of Professor C. R. Rao Is Going To Come Out Soon.
Book Synopsis Introduction to Statistical Inference by : Jack C. Kiefer
Download or read book Introduction to Statistical Inference written by Jack C. Kiefer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is based upon lecture notes developed by Jack Kiefer for a course in statistical inference he taught at Cornell University. The notes were distributed to the class in lieu of a textbook, and the problems were used for homework assignments. Relying only on modest prerequisites of probability theory and cal culus, Kiefer's approach to a first course in statistics is to present the central ideas of the modem mathematical theory with a minimum of fuss and formality. He is able to do this by using a rich mixture of examples, pictures, and math ematical derivations to complement a clear and logical discussion of the important ideas in plain English. The straightforwardness of Kiefer's presentation is remarkable in view of the sophistication and depth of his examination of the major theme: How should an intelligent person formulate a statistical problem and choose a statistical procedure to apply to it? Kiefer's view, in the same spirit as Neyman and Wald, is that one should try to assess the consequences of a statistical choice in some quan titative (frequentist) formulation and ought to choose a course of action that is verifiably optimal (or nearly so) without regard to the perceived "attractiveness" of certain dogmas and methods.
Book Synopsis Statistical Theory and Method Abstracts by :
Download or read book Statistical Theory and Method Abstracts written by and published by . This book was released on 1990 with total page 1070 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Equivalent Measurements, Observability, and Calibration Accuracy Limits in Linear Estimation by : Luigi S. Cicolani
Download or read book Equivalent Measurements, Observability, and Calibration Accuracy Limits in Linear Estimation written by Luigi S. Cicolani and published by . This book was released on 1971 with total page 92 pages. Available in PDF, EPUB and Kindle. Book excerpt: The structure of the linear estimation problem is investigated. First, data compression, performance analysis, and information separation are examined in the case of processing arbitrary sets of measurements. Second, the measurements are limited to samplings of given data types so that properties of the data types are common to any sampling. Thus, the unknowns to be estimated can be reduced to those observable to the data types. Finally, estimation is intended to compare an unknown system to internationally defined physical units. Measurements separate into comparisons with physical units (calibrations) and comparisons among unknowns. Generally, measurements are of the second type and their processing compares the unknown system to intermediate physical standards which appear as unobservable parameters that limit the achievable estimation accuracy.
Book Synopsis Linear Models in Statistics by : Alvin C. Rencher
Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Author :Francisco J. Samaniego Publisher :Springer Science & Business Media ISBN 13 :1441959416 Total Pages :235 pages Book Rating :4.4/5 (419 download)
Book Synopsis A Comparison of the Bayesian and Frequentist Approaches to Estimation by : Francisco J. Samaniego
Download or read book A Comparison of the Bayesian and Frequentist Approaches to Estimation written by Francisco J. Samaniego and published by Springer Science & Business Media. This book was released on 2010-06-14 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The main theme of this monograph is “comparative statistical inference. ” While the topics covered have been carefully selected (they are, for example, restricted to pr- lems of statistical estimation), my aim is to provide ideas and examples which will assist a statistician, or a statistical practitioner, in comparing the performance one can expect from using either Bayesian or classical (aka, frequentist) solutions in - timation problems. Before investing the hours it will take to read this monograph, one might well want to know what sets it apart from other treatises on comparative inference. The two books that are closest to the present work are the well-known tomes by Barnett (1999) and Cox (2006). These books do indeed consider the c- ceptual and methodological differences between Bayesian and frequentist methods. What is largely absent from them, however, are answers to the question: “which - proach should one use in a given problem?” It is this latter issue that this monograph is intended to investigate. There are many books on Bayesian inference, including, for example, the widely used texts by Carlin and Louis (2008) and Gelman, Carlin, Stern and Rubin (2004). These books differ from the present work in that they begin with the premise that a Bayesian treatment is called for and then provide guidance on how a Bayesian an- ysis should be executed. Similarly, there are many books written from a classical perspective.
Book Synopsis Stochastic Models: Estimation and Control: v. 1 by : Maybeck
Download or read book Stochastic Models: Estimation and Control: v. 1 written by Maybeck and published by Academic Press. This book was released on 1979-07-17 with total page 445 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic Models: Estimation and Control: v. 1
Download or read book NASA Technical Note written by and published by . This book was released on 1971 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Best Linear Unbiased Estimators in Continuous Time Regression Models by : Holger Dette
Download or read book Best Linear Unbiased Estimators in Continuous Time Regression Models written by Holger Dette and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Latent Variable Modeling and Applications to Causality by : Maia Berkane
Download or read book Latent Variable Modeling and Applications to Causality written by Maia Berkane and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume gathers refereed papers presented at the 1994 UCLA conference on "La tent Variable Modeling and Application to Causality. " The meeting was organized by the UCLA Interdivisional Program in Statistics with the purpose of bringing together a group of people who have done recent advanced work in this field. The papers in this volume are representative of a wide variety of disciplines in which the use of latent variable models is rapidly growing. The volume is divided into two broad sections. The first section covers Path Models and Causal Reasoning and the papers are innovations from contributors in disciplines not traditionally associated with behavioural sciences, (e. g. computer science with Judea Pearl and public health with James Robins). Also in this section are contri butions by Rod McDonald and Michael Sobel who have a more traditional approach to causal inference, generating from problems in behavioural sciences. The second section encompasses new approaches to questions of model selection with emphasis on factor analysis and time varying systems. Amemiya uses nonlinear factor analysis which has a higher order of complexity associated with the identifiability condi tions. Muthen studies longitudinal hierarchichal models with latent variables and treats the time vector as a variable rather than a level of hierarchy. Deleeuw extends exploratory factor analysis models by including time as a variable and allowing for discrete and ordi nal latent variables. Arminger looks at autoregressive structures and Bock treats factor analysis models for categorical data.
Book Synopsis Discrete Stochastic Processes and Optimal Filtering by : Jean-Claude Bertein
Download or read book Discrete Stochastic Processes and Optimal Filtering written by Jean-Claude Bertein and published by John Wiley & Sons. This book was released on 2012-12-27 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from the extraction of noise signals. Moreover, it is a fundamental feature in a range of applications, such as in navigation in aerospace and aeronautics, filter processing in the telecommunications industry, etc. This book provides a comprehensive overview of this area, discussing random and Gaussian vectors, outlining the results necessary for the creation of Wiener and adaptive filters used for stationary signals, as well as examining Kalman filters which are used in relation to non-stationary signals. Exercises with solutions feature in each chapter to demonstrate the practical application of these ideas using MATLAB.
Book Synopsis Chaotic Systems by : Christos H. Skiadas
Download or read book Chaotic Systems written by Christos H. Skiadas and published by World Scientific. This book was released on 2010 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains a collection of papers suggested by the Scientific Committee that includes the best papers presented in the 2nd International Conference (CHAOS2009) on Chaotic Modeling, Simulation and Applications, that was held in Chania, Crete, Greece, June 1-5, 2009. The aim of the conference was to invite and bring together people working in interesting topics of chaotic modeling, nonlinear and dynamical systems and chaotic simulation. The volume presents theoretical and applied contributions on chaotic systems. Papers from several nonlinear analysis and chaotic fields are included and new and very important results are presented. Emphasis was given to the selection of works that have significant impact in the chaotic field and open new horizons to further develop related topics and subjects. Even more the selected papers are addressed to an interdisciplinary audience aiming at the broad dissemination of the theory and practice of chaotic modeling and simulation and nonlinear science.
