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Model Misspecification Tests Of Regression Functions
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Book Synopsis Model Misspecification Tests of Regression Functions by : Kiho Jeong
Download or read book Model Misspecification Tests of Regression Functions written by Kiho Jeong and published by . This book was released on 1991 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Implementation and Constructive Use of Misspecification Tests in Econometrics by : L. G. Godfrey
Download or read book The Implementation and Constructive Use of Misspecification Tests in Econometrics written by L. G. Godfrey and published by Manchester University Press. This book was released on 1992 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a collection of papers co-authored by members of the Department of Economics and Related Studies and the Institute for Research in the Social Sciences at the University of York, which deals with methods for calculating asymptotically valid tests for use with samples of the size available in empirical economics. The papers also address the scope for using test statistics to determine the nature of specification errors and for providing suitable corrections to estimates or parameters.
Book Synopsis Misspecification Tests in Econometrics by : L. G. Godfrey
Download or read book Misspecification Tests in Econometrics written by L. G. Godfrey and published by Cambridge University Press. This book was released on 1988 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Misspecification tests play an important role in detecting unreliable and inadequate economic models. This book brings together many results from the growing literature in econometrics on misspecification testing. It provides theoretical analyses and convenient methods for application. The main emphasis is on the Lagrange multiplier principle, which provides considerable unification, although several other approaches are also considered. The author also examines general checks for model adequacy that do not involve formulation of an alternative hypothesis. General and specific tests are discussed in the context of multiple regression models, systems of simultaneous equations, and models with qualitative or limited dependent variables.
Book Synopsis The Linear Regression Model Under Test by : W. Kraemer
Download or read book The Linear Regression Model Under Test written by W. Kraemer and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph grew out of joint work with various dedicated colleagues and students at the Vienna Institute for Advanced Studies. We would probably never have begun without the impetus of Johann Maurer, who for some time was the spiritus rector behind the Institute's macromodel of the Austrian economy. Manfred Deistler provided sustained stimulation for our research through many discussions in his econometric research seminar. Similar credits are due to Adrian Pagan, Roberto Mariano and Garry Phillips, the econometrics guest professors at the Institute in the 1982 - 1984 period, who through their lectures and advice have contributed greatly to our effort. Hans SchneeweiB offered helpful comments on an earlier version of the manuscript, and Benedikt Poetscher was always willing to lend a helping . hand when we had trouble with the mathematics of the tests. Needless to say that any errors are our own. Much of the programming for the tests and for the Monte Carlo experiments was done by Petr Havlik, Karl Kontrus and Raimund Alt. Without their assistance, our research project would have been impossible. Petr Havlik and Karl Kontrus in addition. read and criticized portions of the manuscript, and were of great help in reducing our error rate. Many of the more theoretical results in this monograph would never have come to light without the mathematical expertise of Werner Ploberger, who provided most of the statistical background of the chapter on testing for structural change . .
Book Synopsis Omitted Variables and Misspecification Testing Using Auxiliary Regressions by : Aris Spanos
Download or read book Omitted Variables and Misspecification Testing Using Auxiliary Regressions written by Aris Spanos and published by . This book was released on 1985 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Misspecification Analysis by : Theo K. Dijkstra
Download or read book Misspecification Analysis written by Theo K. Dijkstra and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 139 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Information Matrices in Estimating Function Approach by : Qian Zhou
Download or read book Information Matrices in Estimating Function Approach written by Qian Zhou and published by . This book was released on 2009 with total page 174 pages. Available in PDF, EPUB and Kindle. Book excerpt: Estimating functions have been widely used for parameter estimation in various statistical problems. Regular estimating functions produce parameter estimators which have desirable properties, such as consistency and asymptotic normality. In quasi-likelihood inference, an important example of estimating functions, correct specification of the first two moments of the underlying distribution leads to the information unbiasedness, which states that two forms of the information matrix: the negative sensitivity matrix (negative expectation of the first order derivative of an estimating function) and the variability matrix (variance of an estimating function) are equal, or in other words, the analogue of the Fisher information is equivalent to the Godambe information. Consequently, the information unbiasedness indicates that the model-based covariance matrix estimator and sandwich covariance matrix estimator are equivalent. By comparing the model-based and sandwich variance estimators, we propose information ratio (IR) statistics for testing model misspecification of variance/covariance structure under correctly specified mean structure, in the context of linear regression models, generalized linear regression models and generalized estimating equations. Asymptotic properties of the IR statistics are discussed. In addition, through intensive simulation studies, we show that the IR statistics are powerful in various applications: test for heteroscedasticity in linear regression models, test for overdispersion in count data, and test for misspecified variance function and/or misspecified working correlation structure. Moreover, the IR statistics appear more powerful than the classical information matrix test proposed by White (1982). In the literature, model selection criteria have been intensively discussed, but almost all of them target choosing the optimal mean structure. In this thesis, two model selection procedures are proposed for selecting the optimal variance/covariance structure among a collection of candidate structures.
Book Synopsis Some Simple Non-parametric Tests for Misspecification of Regression Models Using Sign Changes of Residuals by : H. Bunzel
Download or read book Some Simple Non-parametric Tests for Misspecification of Regression Models Using Sign Changes of Residuals written by H. Bunzel and published by . This book was released on 1988 with total page 20 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Statistical Tools for Nonlinear Regression by : Sylvie Huet
Download or read book Statistical Tools for Nonlinear Regression written by Sylvie Huet and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Tools for Nonlinear Regression presents methods for analyzing data. It has been expanded to include binomial, multinomial and Poisson non-linear models. The examples are analyzed with the free software nls2 updated to deal with the new models included in the second edition. The nls2 package is implemented in S-PLUS and R. Several additional tools are included in the package for calculating confidence regions for functions of parameters or calibration intervals, using classical methodology or bootstrap.
Book Synopsis Using Sample Survey Weights to Test for Misspecification in a Linear Regression Model by : William H. DuMouchel
Download or read book Using Sample Survey Weights to Test for Misspecification in a Linear Regression Model written by William H. DuMouchel and published by . This book was released on 1976 with total page 27 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Analyzing Uniform Residuals for Misspecification of a Linear Regression Model by : C. P. Quesenberry
Download or read book Analyzing Uniform Residuals for Misspecification of a Linear Regression Model written by C. P. Quesenberry and published by . This book was released on 1982 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linearity and Misspecification Tests for Vector Smooth Transition Regression Models by : Timo Teräsvirta
Download or read book Linearity and Misspecification Tests for Vector Smooth Transition Regression Models written by Timo Teräsvirta and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Linear Models in Statistics by : Alvin C. Rencher
Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Book Synopsis The Gradient Test by : Artur Lemonte
Download or read book The Gradient Test written by Artur Lemonte and published by Academic Press. This book was released on 2016-02-05 with total page 157 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Gradient Test: Another Likelihood-Based Test presents the latest on the gradient test, a large-sample test that was introduced in statistics literature by George R. Terrell in 2002. The test has been studied by several authors, is simply computed, and can be an interesting alternative to the classical large-sample tests, namely, the likelihood ratio (LR), Wald (W), and Rao score (S) tests. Due to the large literature about the LR, W and S tests, the gradient test is not frequently used to test hypothesis. The book covers topics on the local power of the gradient test, the Bartlett-corrected gradient statistic, the gradient statistic under model misspecification, and the robust gradient-type bounded-influence test. Covers the background of the gradient statistic and the different models Discusses The Bartlett-corrected gradient statistic Explains the algorithm to compute the gradient-type statistic
Book Synopsis Regression Analysis of Count Data by : A. Colin Cameron
Download or read book Regression Analysis of Count Data written by A. Colin Cameron and published by Cambridge University Press. This book was released on 1998-09-28 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: This analysis provides a comprehensive account of models and methods to interpret frequency data.
Book Synopsis Introductory Econometrics by : Hamid Seddighi
Download or read book Introductory Econometrics written by Hamid Seddighi and published by Routledge. This book was released on 2013-03-01 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the first serious attempt to explain the basics of econometrics and its applications in the clearest and simplest manner possible. Recognising the fact that a good level of mathematics is no longer a necessary prerequisite for economics/financial economics undergraduate and postgraduate programmes, it introduces this key subdivision of economics to an audience who might otherwise have been deterred by its complex nature.
Book Synopsis Minimax Robust Designs for Misspecified Regression Models by : Peilin Shi
Download or read book Minimax Robust Designs for Misspecified Regression Models written by Peilin Shi and published by . This book was released on 2002 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Minimax robust designs are studied for regression models with possible misspecified response functions. These designs, minimizing the maximum of the mean squared error matrix, can control the bias caused by model misspecification and the desired efficiency through one parameter. Using nonsmooth optimization technique, we derive the minimax designs analytically for misspecified regression models. This extends the results in Heo, Schmuland and Wiens (2001). Several examples are discussed for approximately polynomial regression.