Autoregressive Model Inference In Finite Samples
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Autoregressive Model Inference In Finite Samples
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Author : Hans Einar Wensink
language : en
Publisher:
Release Date : 1996
Autoregressive Model Inference In Finite Samples written by Hans Einar Wensink and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Mathematics categories.
Studies In Asymptotic And Finite Sample Inference Of Nonstationary And Nearly Nonstationary Autoregressive Models
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Author : Juha Antti Ahtola
language : en
Publisher:
Release Date : 1983
Studies In Asymptotic And Finite Sample Inference Of Nonstationary And Nearly Nonstationary Autoregressive Models written by Juha Antti Ahtola and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1983 with Mathematical statistics categories.
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing
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Author : Dufour, Jean-Marie
language : en
Publisher: Montréal : CIRANO
Release Date : 2005
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing written by Dufour, Jean-Marie and has been published by Montréal : CIRANO this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Autoregression (Statistics) categories.
Essays On Finite Sample Inference And Financial Econometrics
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Author : Yong Bao
language : en
Publisher:
Release Date : 2004
Essays On Finite Sample Inference And Financial Econometrics written by Yong Bao and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Econometric models categories.
Markovian Processes Two Sided Autoregressions And Finite Sample Inference For Stationary And Nonstationary Autoregressive Processes
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Author : Jean-Marie Dufour
language : en
Publisher:
Release Date : 1999
Markovian Processes Two Sided Autoregressions And Finite Sample Inference For Stationary And Nonstationary Autoregressive Processes written by Jean-Marie Dufour and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing
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Author : Jean-Marie Dufour
language : en
Publisher: Centre interuniversitaire de recherche en économie quantitative
Release Date : 2005*
Finite Sample Simulation Based Inference In Var Models With Applications To Order Selection And Causality Testing written by Jean-Marie Dufour and has been published by Centre interuniversitaire de recherche en économie quantitative this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005* with Autoregression (Statistics) categories.
Seemingly Unrelated Regression Equations Models
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Author : Virendera K. Srivastava
language : en
Publisher: CRC Press
Release Date : 2020-08-14
Seemingly Unrelated Regression Equations Models written by Virendera K. Srivastava and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-14 with Mathematics categories.
This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.
Topics In Autoregression Microform
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Author : Ying Zhang
language : en
Publisher: National Library of Canada = Bibliothèque nationale du Canada
Release Date : 2002
Topics In Autoregression Microform written by Ying Zhang and has been published by National Library of Canada = Bibliothèque nationale du Canada this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Autoregression (Statistics) categories.
An overview of the thesis is given in Chapter 1. Chapter 2 discusses a symbolic form for the exact maximum likelihood estimator in the stationary normal AR(1) process. We derive the finite sample inference properties of the exact maximum likelihood estimator. We establish its consistency and its empirical cumulative distribution for a random walk case. The power of our one-tail unit root test overall outperforms that of previous proposals in the unknown mean AR(1) model. Chapter 3 provides a general technique to describe the shape of the admissible region of AR(p). As applications, we have visualized the admissible regions for AR(3) and AR(4). For the AR(4) process, all possible subset admissible regions for the model re-parametrized in terms of partial autocorrelations are obtained and it is demonstrated that these regions are quite complex and hence this re-parameterization is not so useful in the subset case. Chapter 4 develops an algorithm for computing the expectations of time series products given the autocovariance function. Using it as our tool, we evaluate the bias and variance of the Burg estimate to order n-1 in the first order autoregressive model and find that Burg estimate and the least-squares estimate have the same bias and variance to order n-1 in that case. We also obtain explicit formulae for the large sample bias of Burg estimates in the second order cases. Both simulations and theory indicates that Burg estimates have biases similar to the least-squares estimates in the second order cases. The advantages of the Burg estimates over the least-squares estimates are briefly indicated. Chapter 5 is an extension of Chapter 3. A new more computationally efficient general purpose algorithm for computing the exact maximum likelihood estimates in an AR(p) model is developed. Then this algorithm is used to develop a new approach to subset autoregression modelling in which the subsets are obtained by containing some of the zeta parameters to zero. After the exact maximum likelihood estimation algorithm for the subset models is presented, it is shown how a tentative identification of possible subset AR models can be accomplished using the AIC or BIC criterion and the partial autocorrelation function. The distribution of the residual autocorrelations for subset AR models is also derived and appropriate diagnostic checks for model adequacy are discussed. Several illustrative examples are presented.
International Bibliography Of Economics 1998
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Author : Compiled by the British Library of Political and Economic Science
language : en
Publisher: Psychology Press
Release Date : 1999-12-16
International Bibliography Of Economics 1998 written by Compiled by the British Library of Political and Economic Science and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-12-16 with Business & Economics categories.
Renowned for its international coverage and rigorous selection procedures, this series provides the most comprehensive and scholarly bibliographic service available in the social sciences. Arranged by topic and indexed by author, subject and place-name, each bibliography lists and annotates the most important works published in its field during the year of 1997, including hard-to-locate journal articles. Each volume also includes a complete list of the periodicals consulted.
Simulation Based Inference In Econometrics
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Author : Roberto Mariano
language : en
Publisher: Cambridge University Press
Release Date : 2000-07-20
Simulation Based Inference In Econometrics written by Roberto Mariano and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-07-20 with Business & Economics categories.
This substantial volume has two principal objectives. First it provides an overview of the statistical foundations of Simulation-based inference. This includes the summary and synthesis of the many concepts and results extant in the theoretical literature, the different classes of problems and estimators, the asymptotic properties of these estimators, as well as descriptions of the different simulators in use. Second, the volume provides empirical and operational examples of SBI methods. Often what is missing, even in existing applied papers, are operational issues. Which simulator works best for which problem and why? This volume will explicitly address the important numerical and computational issues in SBI which are not covered comprehensively in the existing literature. Examples of such issues are: comparisons with existing tractable methods, number of replications needed for robust results, choice of instruments, simulation noise and bias as well as efficiency loss in practice.