Download or read book Aspects of Misspecification in Statistical Models written by Wenxin Jiang and published by . This book was released on 1996 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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.
Download or read book Misspecification in Linear Statistical Modeling written by W. M. Ananda Bandulasiri and published by . This book was released on 2001 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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:
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.
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:
Download or read book Statistical Consequences of Attribute Misspecification in the Rule Space Model written by Seongah Im and published by . This book was released on 2007 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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
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.
Download or read book Applied Linear Statistical Models written by Michael H. Kutner and published by McGraw-Hill/Irwin. This book was released on 2005 with total page 1396 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.
Download or read book Evidential Statistics Model Identification and Science written by Mark Louis Taper and published by Frontiers Media SA. This book was released on 2022-02-15 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Nature of Scientific Evidence written by Mark L. Taper and published by . This book was released on 2004-10 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mark Taper, Subhash Lele and an esteemed group of contributors explore the relationships among hypotheses, models, data and interference on which scientific progress rests in an attempt to develop a new quantitative framework for evidence.
Download or read book Bayesian and Frequentist Regression Methods written by Jon Wakefield and published by Springer Science & Business Media. This book was released on 2013-01-04 with total page 700 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian and Frequentist Regression Methods provides a modern account of both Bayesian and frequentist methods of regression analysis. Many texts cover one or the other of the approaches, but this is the most comprehensive combination of Bayesian and frequentist methods that exists in one place. The two philosophical approaches to regression methodology are featured here as complementary techniques, with theory and data analysis providing supplementary components of the discussion. In particular, methods are illustrated using a variety of data sets. The majority of the data sets are drawn from biostatistics but the techniques are generalizable to a wide range of other disciplines.
Download or read book Model Misspecification and Feature Screening for Ultrahigh Dimensional Data written by Junyi Lin and published by . This book was released on 2011 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Effect of Model Misspecification for Polytomous Logistic Adjacent Category Item Response Theory Models written by Daphna Harel and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "This thesis explores the effect of model misspecification on the estimation of the latent trait in the polytomous logistic adjacent-category models from Item Response Theory (IRT). In any statistical analysis, issues of model misspecification arise whenever the posited model differs from the true data-generating model. In IRT, these issues are of particular importance since the latent trait is only measurable via the posited model.First, a discrimination-parameter weighted summed score is developed to extend the relationship between the summed score and the polytomous Rasch models to a generalized version of the Partial Credit Model (PCM). Theoretical results are developed for the weighted summed score, which show its significance to the problem of ranking respondents. The weighted summed score is then compared to the summed score under both a PCM and a Generalized PCM. The utility of the weighted summed score is illustrated through an analysis of the CES-D Scale used to measure depressive symptomatology.Next, the collapsing of categories is addressed in two ways. First, decision rules are proposed to inform the decision of whether the categories of an item require collapsing. These decision rules are tested for their stability and efficacy in improving estimation of the latent trait via a simulation study. Second, the true model for the collapsed data is defined and shown to not be a member of the logistic adjacent-category class of IRT models. Therefore, fitting a PCM to collapsed data is intentional model misspecification; the properties of the quasi maximum likelihood estimates for the item-level parameters under the misspecified model are explored." --
Download or read book Robustness written by Lars Peter Hansen and published by Princeton University Press. This book was released on 2016-06-28 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: The standard theory of decision making under uncertainty advises the decision maker to form a statistical model linking outcomes to decisions and then to choose the optimal distribution of outcomes. This assumes that the decision maker trusts the model completely. But what should a decision maker do if the model cannot be trusted? Lars Hansen and Thomas Sargent, two leading macroeconomists, push the field forward as they set about answering this question. They adapt robust control techniques and apply them to economics. By using this theory to let decision makers acknowledge misspecification in economic modeling, the authors develop applications to a variety of problems in dynamic macroeconomics. Technical, rigorous, and self-contained, this book will be useful for macroeconomists who seek to improve the robustness of decision-making processes.
Download or read book Nonparametric Statistics and Mixture Models written by David R. Hunter and published by World Scientific. This book was released on 2011 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: This festschrift includes papers authored by many collaborators, colleagues, and students of Professor Thomas P Hettmansperger, who worked in research in nonparametric statistics, rank statistics, robustness, and mixture models during a career that spanned nearly 40 years. It is a broad sample of peer-reviewed, cutting-edge research related to nonparametrics and mixture models.
