Maximum Likelihood Estimation Of Misspecified Models

Author : T. Fomby,R. Carter Hill
Publisher : Elsevier
Page : 280 pages
File Size : 46,8 Mb
Release : 2003-12-12
Category : Business & Economics
ISBN : 0762310758

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Maximum Likelihood Estimation of Misspecified Models by T. Fomby,R. Carter Hill Pdf

Comparative study of pure and pretest estimators for a possibly misspecified two-way error component model / Badi H. Baltagi, Georges Bresson, Alain Pirotte -- Estimation, inference, and specification testing for possibly misspecified quantile regression / Tae-Hwan Kim, Halbert White -- Quasimaximum likelihood estimation with bounded symmetric errors / Douglas Miller, James Eales, Paul Preckel -- Consistent quasi-maximum likelihood estimation with limited information / Douglas Miller, Sang-Hak Lee -- An examination of the sign and volatility switching arch models under alternative distributional assumptions / Mohamed F. Omran, Florin Avram -- estimating a linear exponential density when the weighting matrix and mean parameter vector are functionally related / Chor-yiu Sin -- Testing in GMM models without truncation / Timothy J. Vogelsang -- Bayesian analysis of misspecified models with fixed effects / Tiemen Woutersen -- Tests of common deterministic trend slopes applied to quarterly global temperature data / Thomas B. Fomby, Timothy J. Vogelsang -- The sandwich estimate of variance / James W. Hardin -- Test statistics and critical values in selectivity models / R. Carter Hill, Lee C. Adkins, Keith A. Bender -- Introduction / Thomas B Fomby, R. Carter Hill.

Author : Vance Martin,Stan Hurn,David Harris
Publisher : Cambridge University Press
Page : 925 pages
File Size : 45,6 Mb
Release : 2013
Category : Business & Economics
ISBN : 9780521139816

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Econometric Modelling with Time Series by Vance Martin,Stan Hurn,David Harris Pdf

"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.

Author : Scott R. Eliason
Publisher : SAGE
Page : 100 pages
File Size : 51,9 Mb
Release : 1993
Category : Mathematics
ISBN : 0803941072

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Maximum Likelihood Estimation by Scott R. Eliason Pdf

This is a short introduction to Maximum Likelihood (ML) Estimation. It provides a general modeling framework that utilizes the tools of ML methods to outline a flexible modeling strategy that accommodates cases from the simplest linear models (such as the normal error regression model) to the most complex nonlinear models linking endogenous and exogenous variables with non-normal distributions. Using examples to illustrate the techniques of finding ML estimators and estimates, the author discusses what properties are desirable in an estimator, basic techniques for finding maximum likelihood solutions, the general form of the covariance matrix for ML estimates, the sampling distribution of ML estimators; the use of ML in the normal as well as other distributions, and some useful illustrations of likelihoods.

Author : Daniel Straumann
Publisher : Springer Science & Business Media
Page : 239 pages
File Size : 46,5 Mb
Release : 2006-01-27
Category : Business & Economics
ISBN : 9783540269786

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Estimation in Conditionally Heteroscedastic Time Series Models by Daniel Straumann Pdf

In his seminal 1982 paper, Robert F. Engle described a time series model with a time-varying volatility. Engle showed that this model, which he called ARCH (autoregressive conditionally heteroscedastic), is well-suited for the description of economic and financial price. Nowadays ARCH has been replaced by more general and more sophisticated models, such as GARCH (generalized autoregressive heteroscedastic). This monograph concentrates on mathematical statistical problems associated with fitting conditionally heteroscedastic time series models to data. This includes the classical statistical issues of consistency and limiting distribution of estimators. Particular attention is addressed to (quasi) maximum likelihood estimation and misspecified models, along to phenomena due to heavy-tailed innovations. The used methods are based on techniques applied to the analysis of stochastic recurrence equations. Proofs and arguments are given wherever possible in full mathematical rigour. Moreover, the theory is illustrated by examples and simulation studies.

Author : Theo K. Dijkstra
Publisher : Springer Science & Business Media
Page : 139 pages
File Size : 52,8 Mb
Release : 2012-12-06
Category : Business & Economics
ISBN : 9783642954610

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Misspecification Analysis by Theo K. Dijkstra Pdf

Author : Xiaohong Chen,Norman R. Swanson
Publisher : Springer Science & Business Media
Page : 582 pages
File Size : 40,9 Mb
Release : 2012-08-01
Category : Business & Economics
ISBN : 9781461416531

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Recent Advances and Future Directions in Causality, Prediction, and Specification Analysis by Xiaohong Chen,Norman R. Swanson Pdf

This book is a collection of articles that present the most recent cutting edge results on specification and estimation of economic models written by a number of the world’s foremost leaders in the fields of theoretical and methodological econometrics. Recent advances in asymptotic approximation theory, including the use of higher order asymptotics for things like estimator bias correction, and the use of various expansion and other theoretical tools for the development of bootstrap techniques designed for implementation when carrying out inference are at the forefront of theoretical development in the field of econometrics. One important feature of these advances in the theory of econometrics is that they are being seamlessly and almost immediately incorporated into the “empirical toolbox” that applied practitioners use when actually constructing models using data, for the purposes of both prediction and policy analysis and the more theoretically targeted chapters in the book will discuss these developments. Turning now to empirical methodology, chapters on prediction methodology will focus on macroeconomic and financial applications, such as the construction of diffusion index models for forecasting with very large numbers of variables, and the construction of data samples that result in optimal predictive accuracy tests when comparing alternative prediction models. Chapters carefully outline how applied practitioners can correctly implement the latest theoretical refinements in model specification in order to “build” the best models using large-scale and traditional datasets, making the book of interest to a broad readership of economists from theoretical econometricians to applied economic practitioners.

Author : Russell B. Millar
Publisher : John Wiley & Sons
Page : 286 pages
File Size : 49,8 Mb
Release : 2011-07-26
Category : Mathematics
ISBN : 9781119977711

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Maximum Likelihood Estimation and Inference by Russell B. Millar Pdf

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 : Halbert White
Publisher : Cambridge University Press
Page : 396 pages
File Size : 51,7 Mb
Release : 1996-06-28
Category : Business & Economics
ISBN : 0521574463

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Estimation, Inference and Specification Analysis by Halbert White Pdf

This book examines the consequences of misspecifications for the interpretation of likelihood-based methods of statistical estimation and interference. The analysis concludes with an examination of methods by which the possibility of misspecification can be empirically investigated.

Author : Anonim
Publisher : Academic Press
Page : 650 pages
File Size : 45,8 Mb
Release : 2017-12-13
Category : Technology & Engineering
ISBN : 9780128118887

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Academic Press Library in Signal Processing, Volume 7 by Anonim Pdf

Academic Press Library in Signal Processing, Volume 7: Array, Radar and Communications Engineering is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in Array and Radar Processing, Communications Engineering and Machine Learning. Users will find the book to be an invaluable starting point to their research and initiatives. With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved. Presents a quick tutorial of reviews of important and emerging topics of research Explores core principles, technologies, algorithms and applications Edited and contributed by international leading figures in the field Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge

Author : William Gould,Jeffrey Pitblado,William Sribney
Publisher : Stata Press
Page : 312 pages
File Size : 45,7 Mb
Release : 2006
Category : Computers
ISBN : 9781597180122

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Maximum Likelihood Estimation with Stata, Third Edition by William Gould,Jeffrey Pitblado,William Sribney Pdf

Written by the creators of Stata's likelihood maximization features, Maximum Likelihood Estimation with Stata, Third Edition continues the pioneering work of the previous editions. Emphasizing practical implications for applied work, the first chapter provides an overview of maximum likelihood estimation theory and numerical optimization methods. With step-by-step instructions, the next several chapters detail the use of Stata to maximize user-written likelihood functions. Various examples include logit, probit, linear, Weibull, and random-effects linear regression as well as the Cox proportional hazards model. The final chapters describe how to add a new estimation command to Stata. Assuming a familiarity with Stata, this reference is ideal for researchers who need to maximize their own likelihood functions. New ml commands and their functions: constraint: fits a model with linear constraints on the coefficient by defining your constraints; accepts a constraint matrix ml model: picks up survey characteristics; accepts the subpop option for analyzing survey data optimization algorithms: Berndt-Hall-Hall-Hausman (BHHH), Davidon-Fletcher-Powell (DFP), Broyden-Fletcher-Goldfarb-Shanno (BFGS) ml: switches between optimization algorithms; computes variance estimates using the outer product of gradients (OPG)

Author : E. M. Tiit,T. Kollo,H. Niemi
Publisher : Walter de Gruyter GmbH & Co KG
Page : 352 pages
File Size : 46,9 Mb
Release : 2020-05-18
Category : Mathematics
ISBN : 9783112314210

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Multivariate Statistics and Matrices in Statistics by E. M. Tiit,T. Kollo,H. Niemi Pdf

No detailed description available for "Multivariate Statistics and Matrices in Statistics".

Author : Nico J.D. Nagelkerke
Publisher : Springer Science & Business Media
Page : 118 pages
File Size : 42,7 Mb
Release : 2012-12-06
Category : Mathematics
ISBN : 9781461228585

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Maximum Likelihood Estimation of Functional Relationships by Nico J.D. Nagelkerke Pdf

The theory of functional relationships concerns itself with inference from models with a more complex error structure than those existing in regression models. We are familiar with the bivariate linear relationship having measurement errors in both variables and the fact that the standard regression estimator of the slope underestimates the true slope. One complication with inference about parameters in functional relationships, is that many of the standard properties of likelihood theory do not apply, at least not in the form in which they apply to e.g. regression models. This is probably one of the reasons why these models are not adequately discussed in most general books on statistics, despite their wide applicability. In this monograph we will explore the properties of likelihood methods in the context of functional relationship models. Full and conditional likelihood methods are both considered. Possible modifications to these methods are considered when necessary. Apart from exloring the theory itself, emphasis shall be placed upon the derivation of useful estimators and their second moment properties. No attempt is made to be mathematically rigid. Proofs are usually outlined with extensive use of the Landau 0(.) and 0(.) notations. It is hoped that this shall provide more insight than the inevitably lengthy proofs meeting strict standards of mathematical rigour.

Author : L. G. Godfrey
Publisher : Manchester University Press
Page : 402 pages
File Size : 43,9 Mb
Release : 1992
Category : Econometrics
ISBN : 0719032741

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The Implementation and Constructive Use of Misspecification Tests in Econometrics by L. G. Godfrey Pdf

This is a collection of papers co-authored by members of the Department of Economics and Related Studies and the Institute for Research in the Social Sciences at the University of York, which deals with methods for calculating asymptotically valid tests for use with samples of the size available in empirical economics. The papers also address the scope for using test statistics to determine the nature of specification errors and for providing suitable corrections to estimates or parameters.

Author : Stanislav Anatolyev,Nikolay Gospodinov
Publisher : CRC Press
Page : 230 pages
File Size : 41,8 Mb
Release : 2011-06-07
Category : Business & Economics
ISBN : 9781439838266

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Methods for Estimation and Inference in Modern Econometrics by Stanislav Anatolyev,Nikolay Gospodinov Pdf

This book covers important topics in econometrics. It discusses methods for efficient estimation in models defined by unconditional and conditional moment restrictions, inference in misspecified models, generalized empirical likelihood estimators, and alternative asymptotic approximations. The first chapter provides a general overview of established nonparametric and parametric approaches to estimation and conventional frameworks for statistical inference. The next several chapters focus on the estimation of models based on moment restrictions implied by economic theory. The final chapters cover nonconventional asymptotic tools that lead to improved finite-sample inference.

Author : Ludwig Fahrmeir,Gerhard Tutz
Publisher : Springer Science & Business Media
Page : 537 pages
File Size : 50,5 Mb
Release : 2013-03-14
Category : Mathematics
ISBN : 9781475734546

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Multivariate Statistical Modelling Based on Generalized Linear Models by Ludwig Fahrmeir,Gerhard Tutz Pdf

The book is aimed at applied statisticians, graduate students of statistics, and students and researchers with a strong interest in statistics and data analysis. This second edition is extensively revised, especially those sections relating with Bayesian concepts.