Transformations for an Exact Goodness-to-fit Test of Structural Change in the Linear Regression Model PDF Download

Author: Maxwell L. King
Publisher:
ISBN: 9780867467758
Category : Goodness-of-fit tests
Languages : en
Pages : 11

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Author: Walter Krämer
Publisher: Springer Science & Business Media
ISBN: 3642484123
Category : Business & Economics
Languages : en
Pages : 134

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Book Description
Econometric models are made up of assumptions which never exactly match reality. Among the most contested ones is the requirement that the coefficients of an econometric model remain stable over time. Recent years have therefore seen numerous attempts to test for it or to model possible structural change when it can no longer be ignored. This collection of papers from Empirical Economics mirrors part of this development. The point of departure of most studies in this volume is the standard linear regression model Yt = x;fJt + U (t = I, ... , 1), t where notation is obvious and where the index t emphasises the fact that structural change is mostly discussed and encountered in a time series context. It is much less of a problem for cross section data, although many tests apply there as well. The null hypothesis of most tests for structural change is that fJt = fJo for all t, i.e. that the same regression applies to all time periods in the sample and that the disturbances u are well behaved. The well known Chow test for instance assumes t that there is a single structural shift at a known point in time, i.e. that fJt = fJo (t

Author: C. Radhakrishna Rao
Publisher: Springer Science & Business Media
ISBN: 3540742271
Category : Mathematics
Languages : en
Pages : 583

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Book Description
Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.

Author: Harvey Motulsky
Publisher: Oxford University Press
ISBN: 9780198038344
Category : Mathematics
Languages : en
Pages : 352

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Book Description
Most biologists use nonlinear regression more than any other statistical technique, but there are very few places to learn about curve-fitting. This book, by the author of the very successful Intuitive Biostatistics, addresses this relatively focused need of an extraordinarily broad range of scientists.

Author: Jacob Cohen
Publisher: Routledge
ISBN: 1134801017
Category : Psychology
Languages : en
Pages : 666

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Book Description
This classic text on multiple regression is noted for its nonmathematical, applied, and data-analytic approach. Readers profit from its verbal-conceptual exposition and frequent use of examples. The applied emphasis provides clear illustrations of the principles and provides worked examples of the types of applications that are possible. Researchers learn how to specify regression models that directly address their research questions. An overview of the fundamental ideas of multiple regression and a review of bivariate correlation and regression and other elementary statistical concepts provide a strong foundation for understanding the rest of the text. The third edition features an increased emphasis on graphics and the use of confidence intervals and effect size measures, and an accompanying website with data for most of the numerical examples along with the computer code for SPSS, SAS, and SYSTAT, at www.psypress.com/9780805822236 . Applied Multiple Regression serves as both a textbook for graduate students and as a reference tool for researchers in psychology, education, health sciences, communications, business, sociology, political science, anthropology, and economics. An introductory knowledge of statistics is required. Self-standing chapters minimize the need for researchers to refer to previous chapters.

Author: International Monetary Fund Library
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 702

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Author: Raymond J. Carroll
Publisher: Routledge
ISBN: 1351407279
Category : Mathematics
Languages : en
Pages : 264

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Book Description
This monograph provides a careful review of the major statistical techniques used to analyze regression data with nonconstant variability and skewness. The authors have developed statistical techniques--such as formal fitting methods and less formal graphical techniques-- that can be applied to many problems across a range of disciplines, including pharmacokinetics, econometrics, biochemical assays, and fisheries research. While the main focus of the book in on data transformation and weighting, it also draws upon ideas from diverse fields such as influence diagnostics, robustness, bootstrapping, nonparametric data smoothing, quasi-likelihood methods, errors-in-variables, and random coefficients. The authors discuss the computation of estimates and give numerous examples using real data. The book also includes an extensive treatment of estimating variance functions in regression.

Author:
Publisher:
ISBN:
Category : Economics
Languages : en
Pages : 568

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Author:
Publisher:
ISBN:
Category : Classification
Languages : en
Pages : 564

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Author: Stanley Brul
Publisher: Elsevier
ISBN: 1845692942
Category : Technology & Engineering
Languages : en
Pages : 309

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Book Description
Predicting the growth and behaviour of microorganisms in food has long been an aim in food microbiology research. In recent years, microbial models have evolved to become more exact and the discipline of quantitative microbial ecology has gained increasing importance for food safety management, particularly as minimal processing techniques have become more widely used. These processing methods operate closer to microbial death, survival and growth boundaries and therefore require even more precise models. Written by a team of leading experts in the field, Modelling microorganims in food assesses the latest developments and provides an outlook for the future of microbial modelling. Part one discusses general issues involved in building models of microbial growth and inactivation in foods, with chapters on the historical background of the field, experimental design, data processing and model fitting, the problem of uncertainty and variability in models and modelling lag-time. Further chapters review the use of quantitative microbiology tools in predictive microbiology and the use of predictive microbiology in risk assessment. The second part of the book focuses on new approaches in specific areas of microbial modelling, with chapters discussing the implications of microbial variability in predictive modelling and the importance of taking into account microbial interactions in foods. Predicting microbial inactivation under high pressure and the use of mechanistic models are also covered. The final chapters outline the possibility of incorporating systems biology approaches into food microbiology. Modelling microorganisms in food is a standard reference for all those in the field of food microbiology. Assesses the latest developments in microbial modelling Discusses the issues involved in building models of microbial growth Chapters review the use of quantitative microbiology tools in predictive microbiology