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Author: Paul A. Bekker Publisher: Academic Press ISBN: 148321639X Category : Social Science Languages : en Pages : 224
Book Description
Identification, Equivalent Models, and Computer Algebra provides information pertinent to computer algebra. This book presents a brief discussion of the commutation matrix, an operator that plays a role when derivatives have to be evaluated involving symmetric matrices. Organized into eight chapters, this book begins with an overview of the link between identification of a parameter and the existence of a consistent estimator, and the link between identification of a model and the rank of a Jacobian matrix. This text then describes an algorithm for the determination of the exact rank of a parametrized matrix. Other chapters consider the identification in the simultaneous equation model. This book discusses as well the identification assessment in confirmatory factor analysis, a problem related to the simultaneous equations model. The final chapter deals with various computer programs that the enclosed diskette contains. This book is a valuable resource for readers who are interested in computer algebra.
Author: Paul A. Bekker Publisher: Academic Press ISBN: 148321639X Category : Social Science Languages : en Pages : 224
Book Description
Identification, Equivalent Models, and Computer Algebra provides information pertinent to computer algebra. This book presents a brief discussion of the commutation matrix, an operator that plays a role when derivatives have to be evaluated involving symmetric matrices. Organized into eight chapters, this book begins with an overview of the link between identification of a parameter and the existence of a consistent estimator, and the link between identification of a model and the rank of a Jacobian matrix. This text then describes an algorithm for the determination of the exact rank of a parametrized matrix. Other chapters consider the identification in the simultaneous equation model. This book discusses as well the identification assessment in confirmatory factor analysis, a problem related to the simultaneous equations model. The final chapter deals with various computer programs that the enclosed diskette contains. This book is a valuable resource for readers who are interested in computer algebra.
Book Description
This is the first of two volumes containing papers and commentaries presented at the Eleventh World Congress of the Econometric Society, held in Montreal, Canada in August 2015. These papers provide state-of-the-art guides to the most important recent research in economics. The book includes surveys and interpretations of key developments in economics and econometrics, and discussion of future directions for a wide variety of topics, covering both theory and application. These volumes provide a unique, accessible survey of progress on the discipline, written by leading specialists in their fields. The first volume includes theoretical and applied papers addressing topics such as dynamic mechanism design, agency problems, and networks.
Author: Kenneth A. Bollen Publisher: John Wiley & Sons ISBN: 0471011711 Category : Mathematics Languages : en Pages : 528
Book Description
Analysis of Ordinal Categorical Data Alan Agresti Statistical Science Now has its first coordinated manual of methods for analyzing ordered categorical data. This book discusses specialized models that, unlike standard methods underlying nominal categorical data, efficiently use the information on ordering. It begins with an introduction to basic descriptive and inferential methods for categorical data, and then gives thorough coverage of the most current developments, such as loglinear and logit models for ordinal data. Special emphasis is placed on interpretation and application of methods and contains an integrated comparison of the available strategies for analyzing ordinal data. This is a case study work with illuminating examples taken from across the wide spectrum of ordinal categorical applications. 1984 (0 471-89055-3) 287 pp. Regression Diagnostics Identifying Influential Data and Sources of Collinearity David A. Belsley, Edwin Kuh and Roy E. Welsch This book provides the practicing statistician and econometrician with new tools for assessing the quality and reliability of regression estimates. Diagnostic techniques are developed that aid in the systematic location of data points that are either unusual or inordinately influential; measure the presence and intensity of collinear relations among the regression data and help to identify the variables involved in each; and pinpoint the estimated coefficients that are potentially most adversely affected. The primary emphasis of these contributions is on diagnostics, but suggestions for remedial action are given and illustrated. 1980 (0 471-05856-4) 292 pp. Applied Regression Analysis Second Edition Norman Draper and Harry Smith Featuring a significant expansion of material reflecting recent advances, here is a complete and up-to-date introduction to the fundamentals of regression analysis, focusing on understanding the latest concepts and applications of these methods. The authors thoroughly explore the fitting and checking of both linear and nonlinear regression models, using small or large data sets and pocket or high-speed computing equipment. Features added to this Second Edition include the practical implications of linear regression; the Durbin-Watson test for serial correlation; families of transformations; inverse, ridge, latent root and robust regression; and nonlinear growth models. Includes many new exercises and worked examples. 1981 (0 471-02995-5) 709 pp.
Author: Carlo Giannini Publisher: Springer Science & Business Media ISBN: 3662027577 Category : Business & Economics Languages : en Pages : 144
Book Description
1. Introduction 1 2. Identification Analysis and F.I.M.L. Estimation for the K-Mode1 10 3. Identification Analysis and F.I.ML. Estimation for the C-Model 23 4. Identification Analysis and F.I.M.L. Estimation for the AB-Model 32 5. Impulse Response Analysis and Forecast Error Variance Decomposition in SVAR Modeling 44 5 .a Impulse Response Analysis 44 5.b Variance Decomposition (by Antonio Lanzarotti) 51 6. Long-run A-priori Information. Deterministic Components. Cointegration 58 6.a Long-run A-priori Information 58 6.b Deterministic Components 62 6.c Cointegration 65 7. The Working of an AB-Model 71 Annex 1: The Notions ofReduced Form and Structure in Structural VAR Modeling 83 Annex 2: Some Considerations on the Semantics, Choice and Management of the K, C and AB-Models 87 Appendix A 93 Appendix B 96 Appendix C (by Antonio Lanzarotti and Mario Seghelini) 99 Appendix D (by Antonio Lanzarotti and Mario Seghelini) 109 References 128 Foreword In recent years a growing interest in the structural VAR approach (SVAR) has followed the path-breaking works by Blanchard and Watson (1986), Bemanke (1986) and Sims (1986), especially in U.S. applied macroeconometric literature. The approach can be used in two different, partially overlapping directions: the interpretation ofbusiness cycle fluctuations of a small number of significantmacroeconomic variables and the identification of the effects of different policies.
Author: Mark Davis Publisher: Springer Science & Business Media ISBN: 940094828X Category : Science Languages : en Pages : 405
Book Description
This book aims to provide a unified treatment of input/output modelling and of control for discrete-time dynamical systems subject to random disturbances. The results presented are of wide applica bility in control engineering, operations research, econometric modelling and many other areas. There are two distinct approaches to mathematical modelling of physical systems: a direct analysis of the physical mechanisms that comprise the process, or a 'black box' approach based on analysis of input/output data. The second approach is adopted here, although of course the properties ofthe models we study, which within the limits of linearity are very general, are also relevant to the behaviour of systems represented by such models, however they are arrived at. The type of system we are interested in is a discrete-time or sampled-data system where the relation between input and output is (at least approximately) linear and where additive random dis turbances are also present, so that the behaviour of the system must be investigated by statistical methods. After a preliminary chapter summarizing elements of probability and linear system theory, we introduce in Chapter 2 some general linear stochastic models, both in input/output and state-space form. Chapter 3 concerns filtering theory: estimation of the state of a dynamical system from noisy observations. As well as being an important topic in its own right, filtering theory provides the link, via the so-called innovations representation, between input/output models (as identified by data analysis) and state-space models, as required for much contemporary control theory.
Author: Calyampudi R. Rao Publisher: Springer Science & Business Media ISBN: 0387227520 Category : Mathematics Languages : en Pages : 429
Book Description
An up-to-date account of the theory and applications of linear models, for use as a textbook in statistics at graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights include: - a special emphasis on sensitivity analysis and model selection; - a chapter devoted to the analysis of categorical data based on logic, loglinear, and logistic regression models; - a chapter devoted to incomplete data sets; - an extensive appendix on matrix theory; - a chapter devoted to the analysis of categorical data based on a unified presentation of generalized linear models including GEE-methods for correlated response; - a chapter devoted to incomplete data sets including regression diagnostics to identify Non-MCAR-processes The material covered is thus invaluable not only to graduates, but also to researchers and consultants in statistics.
Author: Shayle R. Searle Publisher: ISBN: Category : Mathematics Languages : en Pages : 562
Book Description
Generalized inverse matrices; Distributions and quadratic forms; Regression, or the full rank model; Introducing linear models: regression on dummy variables; Models not of full rank; Two elementary models; The 2-way crossed classification; Some other analysis; Introduction to variance components; Methods of estimating variance components from unbalanced data; Variance component estimation from unbalanced data: formulac; Linear models.
Author: Paul A. Bekker
Author: Paul A. Bekker
Author: 
Author: Bo Honoré
Author: Kenneth A. Bollen
Author: Carlo Giannini
Author: Mark Davis
Author: Calyampudi R. Rao
Author: 
Author: Shayle R. Searle
Author: Neil R. Ericsson