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Author: Chu-An Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper derives the limiting distributions of least squares averaging estimators for linear regression models in a local asymptotic framework. We show that the averaging estimators with fixed weights are asymptotically normal and then develop a plug-in averaging estimator that minimizes the sample analog of the asymptotic mean squared error. We investigate the focused information criterion (Claeskens and Hjort, 2003), the plug-in averaging estimator, the Mallows model averaging estimator (Hansen, 2007), and the jackknife model averaging estimator (Hansen and Racine, 2012). We find that the asymptotic distributions of averaging estimators with data-dependent weights are nonstandard and cannot be approximated by simulation. To address this issue, we propose a simple procedure to construct valid confidence intervals with improved coverage probability. Monte Carlo simulations show that the plug-in averaging estimator generally has smaller expected squared error than other existing model averaging methods, and the coverage probability of proposed confidence intervals achieves the nominal level. As an empirical illustration, the proposed methodology is applied to cross-country growth regressions.
Author: Chu-An Liu
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
This paper derives the limiting distributions of least squares averaging estimators for linear regression models in a local asymptotic framework. We show that the averaging estimators with fixed weights are asymptotically normal and then develop a plug-in averaging estimator that minimizes the sample analog of the asymptotic mean squared error. We investigate the focused information criterion (Claeskens and Hjort, 2003), the plug-in averaging estimator, the Mallows model averaging estimator (Hansen, 2007), and the jackknife model averaging estimator (Hansen and Racine, 2012). We find that the asymptotic distributions of averaging estimators with data-dependent weights are nonstandard and cannot be approximated by simulation. To address this issue, we propose a simple procedure to construct valid confidence intervals with improved coverage probability. Monte Carlo simulations show that the plug-in averaging estimator generally has smaller expected squared error than other existing model averaging methods, and the coverage probability of proposed confidence intervals achieves the nominal level. As an empirical illustration, the proposed methodology is applied to cross-country growth regressions.
Author: P. K. Bhattacharya (Mathematician)
Publisher:
ISBN:
Category : Matrices
Languages : en
Pages : 32
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Book Description
For the linear regression of y on x observations the loss in estimating the true regression function by another function is considered as a loss function. For the loss function, it is shown under certain conditions that if the class of estimates which are linear in y's and have bounded risk is non-empty, then the estimate obtained by the method of least squares belongs to this class and has uniformly minimum risk in this class. A necessary and sufficient condition on the distribution function of x observations is obtained for this class to be non-empty, which unfortunately is not easy to verify in particular cases and is violated in a ver simple situation. owever, by a sequential modification of the sampling scheme, this condition may always be satisfied at the cost of an arbitrarily small increase in the expected sa ple size. I T IS ALSO SHOWN UNDER CERTAIN FURTHER C NDITIONS ON THE FAMILY OF ADMISSIBLE DISTRIB TIONS THAT THE LEAST SQUARES ESTIMATOR IS MINIMAX IN THE CLASS OF ALL ESTIMATORS. (Author).
Author: David Fletcher
Publisher: Springer
ISBN: 3662585413
Category : Mathematics
Languages : en
Pages : 107
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Book Description
This book provides a concise and accessible overview of model averaging, with a focus on applications. Model averaging is a common means of allowing for model uncertainty when analysing data, and has been used in a wide range of application areas, such as ecology, econometrics, meteorology and pharmacology. The book presents an overview of the methods developed in this area, illustrating many of them with examples from the life sciences involving real-world data. It also includes an extensive list of references and suggestions for further research. Further, it clearly demonstrates the links between the methods developed in statistics, econometrics and machine learning, as well as the connection between the Bayesian and frequentist approaches to model averaging. The book appeals to statisticians and scientists interested in what methods are available, how they differ and what is known about their properties. It is assumed that readers are familiar with the basic concepts of statistical theory and modelling, including probability, likelihood and generalized linear models.
Author: Christopher F. Parmeter
Publisher: Emerald Group Publishing
ISBN: 1837978735
Category : Business & Economics
Languages : en
Pages : 487
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Book Description
It is the editor’s distinct privilege to gather this collection of papers that honors Subhal Kumbhakar’s many accomplishments, drawing further attention to the various areas of scholarship that he has touched.
Author: Tore Schweder
Publisher: Cambridge University Press
ISBN: 0521861608
Category : Business & Economics
Languages : en
Pages : 521
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Book Description
This is the first book to develop a methodology of confidence distributions, with a lively mix of theory, illustrations, applications and exercises.
Author: Roger Koenker
Publisher:
ISBN:
Category : Estimation theory
Languages : en
Pages : 36
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Book Description
Author: László Györfi
Publisher: Springer Science & Business Media
ISBN: 0387224424
Category : Mathematics
Languages : en
Pages : 662
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Book Description
This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.
Author: Pierre Perron
Publisher: Montréal : Université de Montréal, Centre de recherche et développement en économique
ISBN: 9782893820934
Category : Distribution (Economic theory)
Languages : en
Pages : 18
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Book Description
Author: Zvi Griliches
Publisher: Elsevier
ISBN: 0444532005
Category : Business & Economics
Languages : en
Pages : 1057
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Book Description
The Handbook is a definitive reference source and teaching aid for econometricians. It examines models, estimation theory, data analysis and field applications in econometrics.
Author: Thomas Kailath
Publisher: Hutchinson Ross Publishing Company
ISBN:
Category : Mathematics
Languages : en
Pages : 344
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Book Description
A survey of the field; Mathematical foundations of least-squares prediction theory; Wiener-hopf equations and optimum filters; State-space models and recursive filters.
