Large Sample Properties of Maximum Likelihood Estimators PDF Download
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Author: Nicholas Herbert Stern
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 28
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Author: Nicholas Herbert Stern
Publisher:
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 28
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Book Description
Author: Vance Martin
Publisher: Cambridge University Press
ISBN: 0521139813
Category : Business & Economics
Languages : en
Pages : 925
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Book Description
"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: Raymond L. Chambers
Publisher: CRC Press
ISBN: 1420011359
Category : Mathematics
Languages : en
Pages : 374
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Book Description
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: Alex McMillan
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 262
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Author: Scott R. Eliason
Publisher: SAGE
ISBN: 9780803941076
Category : Mathematics
Languages : en
Pages : 100
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Book Description
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: Robert Ernest Tarone
Publisher:
ISBN:
Category :
Languages : en
Pages : 190
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Author: Hongjian Yu
Publisher:
ISBN:
Category :
Languages : en
Pages : 194
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Author: Nancy Milena Hoyos Gomez
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Author: Dina Bassiri
Publisher:
ISBN:
Category : Education
Languages : en
Pages : 344
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Author: Diane E. Duffy
Publisher:
ISBN:
Category :
Languages : en
Pages : 50
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Book Description
