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Author : J. Stene
Publisher :
ISBN 13 :
Total Pages : 18 pages
Book Rating : 4.:/5 (897 download)
Download or read book A Property of Fisher's Scoring Method for Maximum Likelihood Estimators written by J. Stene and published by . This book was released on 1968 with total page 18 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Jon Stene
Publisher :
ISBN 13 :
Total Pages : 38 pages
Book Rating : 4.:/5 (471 download)
Download or read book On Fisher's Scoring Method for Maximum Likelihood Estimators written by Jon Stene and published by . This book was released on 1970 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Stephen M. Stigler
Publisher : Harvard University Press
ISBN 13 : 9780674009790
Total Pages : 514 pages
Book Rating : 4.0/5 (97 download)
Download or read book Statistics on the Table written by Stephen M. Stigler and published by Harvard University Press. This book was released on 2002-09-30 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This lively collection of essays examines statistical ideas with an ironic eye for their essence and what their history can tell us for current disputes. The topics range from 17th-century medicine and the circulation of blood, to the cause of the Great Depression, to the determinations of the shape of the Earth and the speed of light.
Author : MANOJ KUMAR SRIVASTAVA
Publisher : PHI Learning Pvt. Ltd.
ISBN 13 : 812034930X
Total Pages : 817 pages
Book Rating : 4.1/5 (23 download)
Download or read book STATISTICAL INFERENCE : THEORY OF ESTIMATION written by MANOJ KUMAR SRIVASTAVA and published by PHI Learning Pvt. Ltd.. This book was released on 2014-04-03 with total page 817 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is sequel to a book Statistical Inference: Testing of Hypotheses (published by PHI Learning). Intended for the postgraduate students of statistics, it introduces the problem of estimation in the light of foundations laid down by Sir R.A. Fisher (1922) and follows both classical and Bayesian approaches to solve these problems. The book starts with discussing the growing levels of data summarization to reach maximal summarization and connects it with sufficient and minimal sufficient statistics. The book gives a complete account of theorems and results on uniformly minimum variance unbiased estimators (UMVUE)—including famous Rao and Blackwell theorem to suggest an improved estimator based on a sufficient statistic and Lehmann-Scheffe theorem to give an UMVUE. It discusses Cramer-Rao and Bhattacharyya variance lower bounds for regular models, by introducing Fishers information and Chapman, Robbins and Kiefer variance lower bounds for Pitman models. Besides, the book introduces different methods of estimation including famous method of maximum likelihood and discusses large sample properties such as consistency, consistent asymptotic normality (CAN) and best asymptotic normality (BAN) of different estimators. Separate chapters are devoted for finding Pitman estimator, among equivariant estimators, for location and scale models, by exploiting symmetry structure, present in the model, and Bayes, Empirical Bayes, Hierarchical Bayes estimators in different statistical models. Systematic exposition of the theory and results in different statistical situations and models, is one of the several attractions of the presentation. Each chapter is concluded with several solved examples, in a number of statistical models, augmented with exposition of theorems and results. KEY FEATURES • Provides clarifications for a number of steps in the proof of theorems and related results., • Includes numerous solved examples to improve analytical insight on the subject by illustrating the application of theorems and results. • Incorporates Chapter-end exercises to review student’s comprehension of the subject. • Discusses detailed theory on data summarization, unbiased estimation with large sample properties, Bayes and Minimax estimation, separately, in different chapters.
Author : Nicholas Herbert Stern
Publisher :
ISBN 13 :
Total Pages : 28 pages
Book Rating : 4.3/5 (91 download)
Download or read book Large Sample Properties of Maximum Likelihood Estimators written by Nicholas Herbert Stern and published by . This book was released on 1980 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Adriaan van den Bos
Publisher : John Wiley & Sons
ISBN 13 : 9780470173855
Total Pages : 296 pages
Book Rating : 4.1/5 (738 download)
Download or read book Parameter Estimation for Scientists and Engineers written by Adriaan van den Bos and published by John Wiley & Sons. This book was released on 2007-08-03 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: The subject of this book is estimating parameters of expectation models of statistical observations. The book describes the most important aspects of the subject for applied scientists and engineers. This group of users is often not aware of estimators other than least squares. Therefore one purpose of this book is to show that statistical parameter estimation has much more to offer than least squares estimation alone. In the approach of this book, knowledge of the distribution of the observations is involved in the choice of estimators. A further advantage of the chosen approach is that it unifies the underlying theory and reduces it to a relatively small collection of coherent, generally applicable principles and notions.
Author : Herman J. Bierens
Publisher : Cambridge University Press
ISBN 13 : 9780521542241
Total Pages : 356 pages
Book Rating : 4.5/5 (422 download)
Download or read book Introduction to the Mathematical and Statistical Foundations of Econometrics written by Herman J. Bierens and published by Cambridge University Press. This book was released on 2004-12-20 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended for use in a rigorous introductory PhD level course in econometrics.
Author : Victor Leiva
Publisher : Academic Press
ISBN 13 : 0128038276
Total Pages : 156 pages
Book Rating : 4.1/5 (28 download)
Download or read book The Birnbaum-Saunders Distribution written by Victor Leiva and published by Academic Press. This book was released on 2015-10-26 with total page 156 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Birnbaum-Saunders Distribution presents the statistical theory, methodology, and applications of the Birnbaum-Saunders distribution, a very flexible distribution for modeling different types of data (mainly lifetime data). The book describes the most recent theoretical developments of this model, including properties, transformations and related distributions, lifetime analysis, and shape analysis. It discusses methods of inference based on uncensored and censored data, goodness-of-fit tests, and random number generation algorithms for the Birnbaum-Saunders distribution, also presenting existing and future applications. - Introduces inference in the Birnbaum-Saunders distribution - Provides a comprehensive review of the statistical theory and methodology of the Birnbaum-Distribution - Discusses different applications of the Birnbaum-Saunders distribution - Explains characterization and the lifetime analysis
Author : Russell B. Millar
Publisher : John Wiley & Sons
ISBN 13 : 1119977711
Total Pages : 286 pages
Book Rating : 4.1/5 (199 download)
Download or read book Maximum Likelihood Estimation and Inference written by Russell B. Millar and published by John Wiley & Sons. This book was released on 2011-07-26 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a fresh look at the popular and well-established method of maximum likelihood for statistical estimation and inference. It begins with an intuitive introduction to the concepts and background of likelihood, and moves through to the latest developments in maximum likelihood methodology, including general latent variable models and new material for the practical implementation of integrated likelihood using the free ADMB software. Fundamental issues of statistical inference are also examined, with a presentation of some of the philosophical debates underlying the choice of statistical paradigm. Key features: Provides an accessible introduction to pragmatic maximum likelihood modelling. Covers more advanced topics, including general forms of latent variable models (including non-linear and non-normal mixed-effects and state-space models) and the use of maximum likelihood variants, such as estimating equations, conditional likelihood, restricted likelihood and integrated likelihood. Adopts a practical approach, with a focus on providing the relevant tools required by researchers and practitioners who collect and analyze real data. Presents numerous examples and case studies across a wide range of applications including medicine, biology and ecology. Features applications from a range of disciplines, with implementation in R, SAS and/or ADMB. Provides all program code and software extensions on a supporting website. Confines supporting theory to the final chapters to maintain a readable and pragmatic focus of the preceding chapters. This book is not just an accessible and practical text about maximum likelihood, it is a comprehensive guide to modern maximum likelihood estimation and inference. It will be of interest to readers of all levels, from novice to expert. It will be of great benefit to researchers, and to students of statistics from senior undergraduate to graduate level. For use as a course text, exercises are provided at the end of each chapter.
Author : James O. Berger
Publisher : IMS
ISBN 13 : 9780940600133
Total Pages : 266 pages
Book Rating : 4.6/5 (1 download)
Download or read book The Likelihood Principle written by James O. Berger and published by IMS. This book was released on 1988 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Michel Denuit
Publisher : Springer Nature
ISBN 13 : 3030258203
Total Pages : 452 pages
Book Rating : 4.0/5 (32 download)
Download or read book Effective Statistical Learning Methods for Actuaries I written by Michel Denuit and published by Springer Nature. This book was released on 2019-09-03 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book summarizes the state of the art in generalized linear models (GLMs) and their various extensions: GAMs, mixed models and credibility, and some nonlinear variants (GNMs). In order to deal with tail events, analytical tools from Extreme Value Theory are presented. Going beyond mean modeling, it considers volatility modeling (double GLMs) and the general modeling of location, scale and shape parameters (GAMLSS). Actuaries need these advanced analytical tools to turn the massive data sets now at their disposal into opportunities. The exposition alternates between methodological aspects and case studies, providing numerical illustrations using the R statistical software. The technical prerequisites are kept at a reasonable level in order to reach a broad readership. This is the first of three volumes entitled Effective Statistical Learning Methods for Actuaries. Written by actuaries for actuaries, this series offers a comprehensive overview of insurance data analytics with applications to P&C, life and health insurance. Although closely related to the other two volumes, this volume can be read independently.
Author : Aris Spanos
Publisher : Cambridge University Press
ISBN 13 : 1107185149
Total Pages : 787 pages
Book Rating : 4.1/5 (71 download)
Download or read book Probability Theory and Statistical Inference written by Aris Spanos and published by Cambridge University Press. This book was released on 2019-09-19 with total page 787 pages. Available in PDF, EPUB and Kindle. Book excerpt: This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Author :
Publisher :
ISBN 13 :
Total Pages : 51 pages
Book Rating : 4.:/5 (227 download)
Download or read book Maximum-Likelihood Estimation and Scoring Under Parametric Constraints written by and published by . This book was released on 2006 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maximum likelihood (ML) estimation is a popular approach in solving many signal processing problems. Many of these problems cannot be solved analytically and so numerical techniques such as the method of scoring are applied. However, in many scenarios, it is desirable to modify the ML problem with the inclusion of additional side information. Often this side information is in the form of parametric constraints which the ML estimate (MLE) must now satisfy. We examine the asymptotic normality of the constrained ML (CML) problem and show that it is still consistent as well as asymptotically efficient (with respect to the constrained Cramer-Rao bound). We also generalize the method of scoring to include the constraints, and satisfy the constraints after each iterate. Convergence properties and examples verify the usefulness of the constrained scoring approach. As a particular example, an alternative and more general CML estimator is developed for the linear model with linear constraints.
Author : R. Darrell Bock
Publisher : John Wiley & Sons
ISBN 13 : 1119716683
Total Pages : 386 pages
Book Rating : 4.1/5 (197 download)
Download or read book Item Response Theory written by R. Darrell Bock and published by John Wiley & Sons. This book was released on 2021-07-21 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: A complete discussion of fundamental and advanced topics in Item Response Theory written by pioneers in the field In Item Response Theory, accomplished psychometricians Darrell Bock and Robert Gibbons deliver a comprehensive and up-to-date exploration of the theoretical foundations and applications of Item Response Theory (IRT). Covering both unidimensional and multidimensional IRT, as well as related adaptive test administration of previously calibrated item banks, the book addresses the growing need for understanding of this topic as the use of IRT spreads to other fields. The first book on the topic that offers a complete and unified treatment of its subject, Item Response Theory prepares researchers and students to understand and apply IRT and multidimensional IRT to fields like education, mental health and marketing. Accessible to first year-graduate students with a foundation in the behavioral or social sciences, basic statistics, and generalized linear models, the book walks readers through everything from the logic of IRT to cutting edge applications of the technique. Readers will also benefit from the inclusion of: • A thorough introduction to the foundations of Item Response Theory, including its logic and origins, model-based measurement, psychological scaling, and classical test theory • An exploration of selected mathematical and statistical results, including points, point sets, and set operations, probability, sampling, and joint, conditional, and marginal probability • Discussions of unidimensional and multidimensional IRT models, including item parameter estimation with binary and polytomous data • Analysis of dimensionality, differential item functioning, and multiple group IRT Perfect for graduate students and researchers studying and working with psychometrics in psychology, quantitative psychology, educational measurement, marketing, and statistics, Item Response Theory will also benefit researchers interested in patient reported outcomes in health research.
Author : Leonhard Held
Publisher : Springer Science & Business Media
ISBN 13 : 3642378870
Total Pages : 381 pages
Book Rating : 4.6/5 (423 download)
Download or read book Applied Statistical Inference written by Leonhard Held and published by Springer Science & Business Media. This book was released on 2013-11-12 with total page 381 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers modern statistical inference based on likelihood with applications in medicine, epidemiology and biology. Two introductory chapters discuss the importance of statistical models in applied quantitative research and the central role of the likelihood function. The rest of the book is divided into three parts. The first describes likelihood-based inference from a frequentist viewpoint. Properties of the maximum likelihood estimate, the score function, the likelihood ratio and the Wald statistic are discussed in detail. In the second part, likelihood is combined with prior information to perform Bayesian inference. Topics include Bayesian updating, conjugate and reference priors, Bayesian point and interval estimates, Bayesian asymptotics and empirical Bayes methods. Modern numerical techniques for Bayesian inference are described in a separate chapter. Finally two more advanced topics, model choice and prediction, are discussed both from a frequentist and a Bayesian perspective. A comprehensive appendix covers the necessary prerequisites in probability theory, matrix algebra, mathematical calculus, and numerical analysis.
Author : Robert Ernest Tarone
Publisher :
ISBN 13 :
Total Pages : 190 pages
Book Rating : 4.:/5 (31 download)
Download or read book Asymptotic Properties of Maximum Likelihood Estimators in the General Sampling Framework, and Some Results in Non-normal Linear Regression written by Robert Ernest Tarone and published by . This book was released on 1974 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Erich L. Lehmann
Publisher : Springer Science & Business Media
ISBN 13 : 0387227288
Total Pages : 610 pages
Book Rating : 4.3/5 (872 download)
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".
