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Author : Warren T. Dent
Publisher :
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4.:/5 (868 download)
Download or read book The Limited Information Maximum Likelihood Estimator Revisited written by Warren T. Dent and published by . This book was released on 1972 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Kimio Morimune
Publisher :
ISBN 13 :
Total Pages : 56 pages
Book Rating : 4.:/5 (31 download)
Download or read book Inadmissibility of the Limited Information Maximum Likelihood Estimator when the Disturbances are Small written by Kimio Morimune and published by . This book was released on 1977 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Vinaitheerthan Renganathan
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (13 download)
Download or read book Maximum Likelihood Estimation and Likelihood Ratio Test Revisited written by Vinaitheerthan Renganathan and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Maximum likelihood Estimation is an important aspect of frequentist approach which was introduced by RA Fisher. Maximum Likelihood estimation method helps us to find the estimator for the unknown population parameter. There are other methods of estimation also available such as Least Square Estimation and Bayesian Estimation methods but Maximum Likelihood Estimation is the widely used method to estimate the parameters. This paper provides an overview of Maximum Likelihood Method with example to calculate a Maximum Likelihood Estimator from a sample data set.
Author : T. Fomby
Publisher : Elsevier
ISBN 13 : 9780762310753
Total Pages : 280 pages
Book Rating : 4.3/5 (17 download)
Download or read book Maximum Likelihood Estimation of Misspecified Models written by T. Fomby and published by Elsevier. This book was released on 2003-12-12 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 : Yoshio Kimura
Publisher :
ISBN 13 :
Total Pages : 17 pages
Book Rating : 4.:/5 (753 download)
Download or read book A Reexamination of the Limited-information Maximum Likelihood Estimation written by Yoshio Kimura and published by . This book was released on 1997 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Stanford University. Institute for Mathematical Studies in the Social Sciences
Publisher :
ISBN 13 :
Total Pages : 73 pages
Book Rating : 4.:/5 (123 download)
Download or read book Evaluation of the Distribution Function of the Limited Information Maximum Likelihood Estimator written by Stanford University. Institute for Mathematical Studies in the Social Sciences and published by . This book was released on 1980 with total page 73 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : W. Dent
Publisher :
ISBN 13 :
Total Pages : 12 pages
Book Rating : 4.:/5 (476 download)
Download or read book Computation of the limited information maximum likelihood estimator written by W. Dent and published by . This book was released on 1973 with total page 12 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Scott R. Eliason
Publisher : SAGE
ISBN 13 : 9780803941076
Total Pages : 100 pages
Book Rating : 4.9/5 (41 download)
Download or read book Maximum Likelihood Estimation written by Scott R. Eliason and published by SAGE. This book was released on 1993 with total page 100 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 :
Publisher :
ISBN 13 :
Total Pages : 106 pages
Book Rating : 4.3/5 (555 download)
Download or read book Forecasting with limited information written by and published by . This book was released on 1974 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Grant H. Hillier
Publisher :
ISBN 13 : 9780867461909
Total Pages : 35 pages
Book Rating : 4.4/5 (619 download)
Download or read book Maximum Likelihood Methods for Systems of Stochastic Linear Equations Revisited. Part II. Constraints on the Parameters written by Grant H. Hillier and published by . This book was released on 1981 with total page 35 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Raymond L. Chambers
Publisher : CRC Press
ISBN 13 : 1420011359
Total Pages : 374 pages
Book Rating : 4.4/5 (2 download)
Download or read book Maximum Likelihood Estimation for Sample Surveys written by Raymond L. Chambers and published by CRC Press. This book was released on 2012-05-02 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sample surveys provide data used by researchers in a large range of disciplines to analyze important relationships using well-established and widely used likelihood methods. The methods used to select samples often result in the sample differing in important ways from the target population and standard application of likelihood methods can lead to
Author : Stanford University. Institute for Mathematical Studies in the Social Sciences
Publisher :
ISBN 13 :
Total Pages : 42 pages
Book Rating : 4.:/5 (123 download)
Download or read book Tables of the Exact Distribution Function of the Limited Information Maximum Likelihood Estimator when the Covariance Matrix is Known written by Stanford University. Institute for Mathematical Studies in the Social Sciences and published by . This book was released on 1978 with total page 42 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Franklin M. Fisher
Publisher :
ISBN 13 :
Total Pages : 10 pages
Book Rating : 4.:/5 (227 download)
Download or read book The Covariance Matrix of the Limited Information Estimator and the Identification Test: Comment written by Franklin M. Fisher and published by . This book was released on 1970 with total page 10 pages. Available in PDF, EPUB and Kindle. Book excerpt: In their article, Liu and Breen propose a new estimator of the large-sample asymptotic covariance matrix for the limited information maximum likelihood estimator in simultaneous equations, and question the interpretation of a statistic used in the past to test overidentifying restrictions. The present paper comments on this matter.
Author : William H. Greene
Publisher :
ISBN 13 : 9781526421036
Total Pages : 0 pages
Book Rating : 4.4/5 (21 download)
Download or read book Maximum Likelihood Estimation written by William H. Greene and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Maximum likelihood (ML) estimation is the foundational platform for modern empirical research. The methodology provides organizing principles for combining observational information and underlying theory to understand the workings of the natural and social environment in the face of uncertainty about the origins and interrelations of those data. Alternatives to ML estimator (MLE) are proposed in comparison to or as modifications of the central methodology. This entry develops the topic of ML estimation from the viewpoints of classical statistics and modern econometrics. It begins with an understanding of the methodology. This departs from a consideration of what is meant by the likelihood function and a useful description of the notion of estimation based on the principle of ML. It then develops the theory of the MLE. The MLE has a set of properties, including consistency and efficiency, which establish it among classes of estimators. These are the basic results that motivate MLE as a method of estimation. This entry examines the topics of inference and hypothesis testing in the ML framework - how to compute standard errors and how to accommodate sampling variability in estimation and testing. It concludes with modern extensions of ML that broaden the framework. Notions of robust estimation and inference, latent heterogeneity in panel data and quasi-ML are also considered. Some practical aspects of ML estimation, such as optimization and maximum simulated likelihood are considered in passing. Examples are woven through the development. This entry introduces the theory, language, and practicalities of the methodology.
Author : K. R. Kadiyala
Publisher :
ISBN 13 :
Total Pages : 19 pages
Book Rating : 4.:/5 (661 download)
Download or read book Optimizing in the Class of Fuller Modified Limited Information Maximum Likelihood Estimators written by K. R. Kadiyala and published by . This book was released on 1992 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : P.P.B. Eggermont
Publisher : Springer Nature
ISBN 13 : 1071612441
Total Pages : 514 pages
Book Rating : 4.0/5 (716 download)
Download or read book Maximum Penalized Likelihood Estimation written by P.P.B. Eggermont and published by Springer Nature. This book was released on 2020-12-15 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book deals with parametric and nonparametric density estimation from the maximum (penalized) likelihood point of view, including estimation under constraints. The focal points are existence and uniqueness of the estimators, almost sure convergence rates for the L1 error, and data-driven smoothing parameter selection methods, including their practical performance. The reader will gain insight into technical tools from probability theory and applied mathematics.
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.
