Quasi-Likelihood And Its Application

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Publisher : Springer Science & Business Media
ISBN 13 : 0387226796
Total Pages : 236 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Quasi-Likelihood And Its Application by : Christopher C. Heyde

Download or read book Quasi-Likelihood And Its Application written by Christopher C. Heyde and published by Springer Science & Business Media. This book was released on 2008-01-08 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first account in book form of all the essential features of the quasi-likelihood methodology, stressing its value as a general purpose inferential tool. The treatment is rather informal, emphasizing essential principles rather than detailed proofs, and readers are assumed to have a firm grounding in probability and statistics at the graduate level. Many examples of the use of the methods in both classical statistical and stochastic process contexts are provided.

Local Polynomial Modelling and Its Applications

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Publisher : Routledge
ISBN 13 : 1351434802
Total Pages : 362 pages
Book Rating : 4.3/5 (514 download)

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Book Synopsis Local Polynomial Modelling and Its Applications by : Jianqing Fan

Download or read book Local Polynomial Modelling and Its Applications written by Jianqing Fan and published by Routledge. This book was released on 2018-05-02 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data-analytic approaches to regression problems, arising from many scientific disciplines are described in this book. The aim of these nonparametric methods is to relax assumptions on the form of a regression function and to let data search for a suitable function that describes the data well. The use of these nonparametric functions with parametric techniques can yield very powerful data analysis tools. Local polynomial modeling and its applications provides an up-to-date picture on state-of-the-art nonparametric regression techniques. The emphasis of the book is on methodologies rather than on theory, with a particular focus on applications of nonparametric techniques to various statistical problems. High-dimensional data-analytic tools are presented, and the book includes a variety of examples. This will be a valuable reference for research and applied statisticians, and will serve as a textbook for graduate students and others interested in nonparametric regression.

Maximum Likelihood Estimation and Inference

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Publisher : John Wiley & Sons
ISBN 13 : 1119977711
Total Pages : 286 pages
Book Rating : 4.1/5 (199 download)

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Book Synopsis Maximum Likelihood Estimation and Inference by : Russell B. Millar

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.

Simultaneous Inference Procedures Using the Method of Quasi-likelihood with an Application to Feedback Models

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Publisher :
ISBN 13 :
Total Pages : 152 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Simultaneous Inference Procedures Using the Method of Quasi-likelihood with an Application to Feedback Models by : Suparni Gunasekera

Download or read book Simultaneous Inference Procedures Using the Method of Quasi-likelihood with an Application to Feedback Models written by Suparni Gunasekera and published by . This book was released on 1992 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Foundations Of Modern Econometrics: A Unified Approach

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Publisher : World Scientific
ISBN 13 : 9811220204
Total Pages : 523 pages
Book Rating : 4.8/5 (112 download)

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Book Synopsis Foundations Of Modern Econometrics: A Unified Approach by : Yongmiao Hong

Download or read book Foundations Of Modern Econometrics: A Unified Approach written by Yongmiao Hong and published by World Scientific. This book was released on 2020-07-13 with total page 523 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern economies are full of uncertainties and risk. Economics studies resource allocations in an uncertain market environment. As a generally applicable quantitative analytic tool for uncertain events, probability and statistics have been playing an important role in economic research. Econometrics is statistical analysis of economic and financial data. In the past four decades or so, economics has witnessed a so-called 'empirical revolution' in its research paradigm, and as the main methodology in empirical studies in economics, econometrics has been playing an important role. It has become an indispensable part of training in modern economics, business and management.This book develops a coherent set of econometric theory, methods and tools for economic models. It is written as a textbook for graduate students in economics, business, management, statistics, applied mathematics, and related fields. It can also be used as a reference book on econometric theory by scholars who may be interested in both theoretical and applied econometrics.

Econometric Modelling with Time Series

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Publisher : Cambridge University Press
ISBN 13 : 0521139813
Total Pages : 925 pages
Book Rating : 4.5/5 (211 download)

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Book Synopsis Econometric Modelling with Time Series by : Vance Martin

Download or read book Econometric Modelling with Time Series written by Vance Martin and published by Cambridge University Press. This book was released on 2013 with total page 925 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.

Statistical Foundations of Actuarial Learning and its Applications

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Publisher : Springer Nature
ISBN 13 : 303112409X
Total Pages : 611 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Statistical Foundations of Actuarial Learning and its Applications by : Mario V. Wüthrich

Download or read book Statistical Foundations of Actuarial Learning and its Applications written by Mario V. Wüthrich and published by Springer Nature. This book was released on 2022-11-22 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book discusses the statistical modeling of insurance problems, a process which comprises data collection, data analysis and statistical model building to forecast insured events that may happen in the future. It presents the mathematical foundations behind these fundamental statistical concepts and how they can be applied in daily actuarial practice. Statistical modeling has a wide range of applications, and, depending on the application, the theoretical aspects may be weighted differently: here the main focus is on prediction rather than explanation. Starting with a presentation of state-of-the-art actuarial models, such as generalized linear models, the book then dives into modern machine learning tools such as neural networks and text recognition to improve predictive modeling with complex features. Providing practitioners with detailed guidance on how to apply machine learning methods to real-world data sets, and how to interpret the results without losing sight of the mathematical assumptions on which these methods are based, the book can serve as a modern basis for an actuarial education syllabus.

Econometric Foundations Pack with CD-ROM

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Publisher : Cambridge University Press
ISBN 13 : 9780521623940
Total Pages : 794 pages
Book Rating : 4.6/5 (239 download)

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Book Synopsis Econometric Foundations Pack with CD-ROM by : Ron Mittelhammer (Prof.)

Download or read book Econometric Foundations Pack with CD-ROM written by Ron Mittelhammer (Prof.) and published by Cambridge University Press. This book was released on 2000-07-28 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text and accompanying CD-ROM develop step by step a modern approach to econometric problems. They are aimed at talented upper-level undergraduates, graduate students, and professionals wishing to acquaint themselves with the pinciples and procedures for information processing and recovery from samples of economic data. The text fully provides an operational understanding of a rich set of estimation and inference tools, including tradional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjuction with the computer to address economic problems.

Linear and Non-Linear Financial Econometrics

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Publisher : BoD – Books on Demand
ISBN 13 : 1839624868
Total Pages : 339 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Linear and Non-Linear Financial Econometrics by : Mehmet Terzioğlu

Download or read book Linear and Non-Linear Financial Econometrics written by Mehmet Terzioğlu and published by BoD – Books on Demand. This book was released on 2021-03-17 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of experimental economics and econometric methods increases with each passing day as data quality and software performance develops. New econometric models are developed by diverging from earlier cliché econometric models with the emergence of specialized fields of study. This book, which is expected to be an extensive and useful reference by bringing together some of the latest developments in the field of econometrics, also contains quantitative examples and problem sets. We thank all the authors who contributed to this book with their studies that provide extensive and accessible explanations of the existing econometric methods.

Mathematical Statistics and Applications

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Publisher : IMS
ISBN 13 : 9780940600577
Total Pages : 532 pages
Book Rating : 4.6/5 (5 download)

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Book Synopsis Mathematical Statistics and Applications by : Marc Moore

Download or read book Mathematical Statistics and Applications written by Marc Moore and published by IMS. This book was released on 2003 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Handbook of Beta Distribution and Its Applications

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Publisher : CRC Press
ISBN 13 : 9780824753962
Total Pages : 594 pages
Book Rating : 4.7/5 (539 download)

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Book Synopsis Handbook of Beta Distribution and Its Applications by : Arjun K. Gupta

Download or read book Handbook of Beta Distribution and Its Applications written by Arjun K. Gupta and published by CRC Press. This book was released on 2004-06-21 with total page 594 pages. Available in PDF, EPUB and Kindle. Book excerpt: A milestone in the published literature on the subject, this first-ever Handbook of Beta Distribution and Its Applications clearly enumerates the properties of beta distributions and related mathematical notions. It summarizes modern applications in a variety of fields, reviews up-and-coming progress from the front lines of statistical research and practice, and demonstrates the applicability of beta distributions in fields such as economics, quality control, soil science, and biomedicine. The book discusses the centrality of beta distributions in Bayesian inference, the beta-binomial model and applications of the beta-binomial distribution, and applications of Dirichlet integrals.

Statistics in the 21st Century

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Publisher : CRC Press
ISBN 13 : 1420035398
Total Pages : 571 pages
Book Rating : 4.4/5 (2 download)

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Book Synopsis Statistics in the 21st Century by : Adrian E. Raftery

Download or read book Statistics in the 21st Century written by Adrian E. Raftery and published by CRC Press. This book was released on 2001-07-09 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume discusses an important area of statistics and highlights the most important statistical advances. It is divided into four sections: statistics in the life and medical sciences, business and social science, the physical sciences and engineering, and theory and methods of statistics.

Nonparametric Regression and Generalized Linear Models

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Publisher : CRC Press
ISBN 13 : 9780412300400
Total Pages : 198 pages
Book Rating : 4.3/5 (4 download)

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Book Synopsis Nonparametric Regression and Generalized Linear Models by : P.J. Green

Download or read book Nonparametric Regression and Generalized Linear Models written by P.J. Green and published by CRC Press. This book was released on 1993-05-01 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a great deal of interest and activity in the general area of nonparametric smoothing in statistics. This monograph concentrates on the roughness penalty method and shows how this technique provides a unifying approach to a wide range of smoothing problems. The method allows parametric assumptions to be realized in regression problems, in those approached by generalized linear modelling, and in many other contexts. The emphasis throughout is methodological rather than theoretical, and it concentrates on statistical and computation issues. Real data examples are used to illustrate the various methods and to compare them with standard parametric approaches. Some publicly available software is also discussed. The mathematical treatment is self-contained and depends mainly on simple linear algebra and calculus. This monograph will be useful both as a reference work for research and applied statisticians and as a text for graduate students and other encountering the material for the first time.

Correlated Data Analysis: Modeling, Analytics, and Applications

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Publisher : Springer Science & Business Media
ISBN 13 : 038771393X
Total Pages : 352 pages
Book Rating : 4.3/5 (877 download)

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Book Synopsis Correlated Data Analysis: Modeling, Analytics, and Applications by : Peter X. -K. Song

Download or read book Correlated Data Analysis: Modeling, Analytics, and Applications written by Peter X. -K. Song and published by Springer Science & Business Media. This book was released on 2007-06-30 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

SAS/STAT 9. 3 User's Guide

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Publisher :
ISBN 13 : 9781607646341
Total Pages : 0 pages
Book Rating : 4.6/5 (463 download)

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Book Synopsis SAS/STAT 9. 3 User's Guide by : Sas Institute

Download or read book SAS/STAT 9. 3 User's Guide written by Sas Institute and published by . This book was released on 2011-07 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The GLIMMIX procedure fits and analyzes generalized linear mixed models (GLMM), models with random effects for data that can be nonnormally distributed. This title is also available online.

Quasi-Likelihood and Its Application

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Publisher :
ISBN 13 : 9781475771039
Total Pages : 252 pages
Book Rating : 4.7/5 (71 download)

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Book Synopsis Quasi-Likelihood and Its Application by : Christopher C. Heyde

Download or read book Quasi-Likelihood and Its Application written by Christopher C. Heyde and published by . This book was released on 2014-01-15 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Parameter Estimation in Stochastic Volatility Models

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Publisher : Springer Nature
ISBN 13 : 3031038614
Total Pages : 634 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Parameter Estimation in Stochastic Volatility Models by : Jaya P. N. Bishwal

Download or read book Parameter Estimation in Stochastic Volatility Models written by Jaya P. N. Bishwal and published by Springer Nature. This book was released on 2022-08-06 with total page 634 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book develops alternative methods to estimate the unknown parameters in stochastic volatility models, offering a new approach to test model accuracy. While there is ample research to document stochastic differential equation models driven by Brownian motion based on discrete observations of the underlying diffusion process, these traditional methods often fail to estimate the unknown parameters in the unobserved volatility processes. This text studies the second order rate of weak convergence to normality to obtain refined inference results like confidence interval, as well as nontraditional continuous time stochastic volatility models driven by fractional Levy processes. By incorporating jumps and long memory into the volatility process, these new methods will help better predict option pricing and stock market crash risk. Some simulation algorithms for numerical experiments are provided.