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Author: David F. Findley Publisher: ISBN: Category : Chi-square test Languages : en Pages : 140
Book Description
Applied work involving statistical modeling frequently leads to situations where models must be compared which are not related to one another by parameter restrictions. In such a situation, log-likelihood ratios of pairs of estimated models do not have a chi-square limiting distribution, and statisticians making model selection decisions frequently resort to rather complicated and subjective comparisons of residuals or other model artifacts to accomplish the selection. This paper gives some theoretical background for the use of the usual log-likelihood ratios for non-nested comparisons. The practical importance of this capability is magnified by the fact that maximized likelihood values are usually available from the software used for estimation. Thus comparisons can often be made quickly. This encourages inventiveness and experimentation by the modeler.
Author: David F. Findley Publisher: ISBN: Category : Chi-square test Languages : en Pages : 140
Book Description
Applied work involving statistical modeling frequently leads to situations where models must be compared which are not related to one another by parameter restrictions. In such a situation, log-likelihood ratios of pairs of estimated models do not have a chi-square limiting distribution, and statisticians making model selection decisions frequently resort to rather complicated and subjective comparisons of residuals or other model artifacts to accomplish the selection. This paper gives some theoretical background for the use of the usual log-likelihood ratios for non-nested comparisons. The practical importance of this capability is magnified by the fact that maximized likelihood values are usually available from the software used for estimation. Thus comparisons can often be made quickly. This encourages inventiveness and experimentation by the modeler.
Author: Wayne A. Fuller Publisher: John Wiley & Sons ISBN: 0470317752 Category : Mathematics Languages : en Pages : 734
Book Description
The subject of time series is of considerable interest, especiallyamong researchers in econometrics, engineering, and the naturalsciences. As part of the prestigious Wiley Series in Probabilityand Statistics, this book provides a lucid introduction to thefield and, in this new Second Edition, covers the importantadvances of recent years, including nonstationary models, nonlinearestimation, multivariate models, state space representations, andempirical model identification. New sections have also been addedon the Wold decomposition, partial autocorrelation, long memoryprocesses, and the Kalman filter. Major topics include: * Moving average and autoregressive processes * Introduction to Fourier analysis * Spectral theory and filtering * Large sample theory * Estimation of the mean and autocorrelations * Estimation of the spectrum * Parameter estimation * Regression, trend, and seasonality * Unit root and explosive time series To accommodate a wide variety of readers, review material,especially on elementary results in Fourier analysis, large samplestatistics, and difference equations, has been included.
Author: Maxwell L. King Publisher: Routledge ISBN: 1351140671 Category : Business & Economics Languages : en Pages : 366
Book Description
Originally published in 1987. This collection of original papers deals with various issues of specification in the context of the linear statistical model. The volume honours the early econometric work of Donald Cochrane, late Dean of Economics and Politics at Monash University in Australia. The chapters focus on problems associated with autocorrelation of the error term in the linear regression model and include appraisals of early work on this topic by Cochrane and Orcutt. The book includes an extensive survey of autocorrelation tests; some exact finite-sample tests; and some issues in preliminary test estimation. A wide range of other specification issues is discussed, including the implications of random regressors for Bayesian prediction; modelling with joint conditional probability functions; and results from duality theory. There is a major survey chapter dealing with specification tests for non-nested models, and some of the applications discussed by the contributors deal with the British National Accounts and with Australian financial and housing markets.
Author: James LeSage Publisher: CRC Press ISBN: 1420064258 Category : Business & Economics Languages : en Pages : 362
Book Description
Although interest in spatial regression models has surged in recent years, a comprehensive, up-to-date text on these approaches does not exist. Filling this void, Introduction to Spatial Econometrics presents a variety of regression methods used to analyze spatial data samples that violate the traditional assumption of independence between observat
Author: G. Arminger Publisher: Springer Science & Business Media ISBN: 9780306448058 Category : Mathematics Languages : en Pages : 592
Book Description
Contributors thoroughly survey the most important statistical models used in empirical reserch in the social and behavioral sciences. Following a common format, each chapter introduces a model, illustrates the types of problems and data for which the model is best used, provides numerous examples that draw upon familiar models or procedures, and includes material on software that can be used to estimate the models studied. This handbook will aid researchers, methodologists, graduate students, and statisticians to understand and resolve common modeling problems.
Author: Paul D. Allison Publisher: SAS Institute ISBN: 1599948842 Category : Computers Languages : en Pages : 337
Book Description
Easy to read and comprehensive, Survival Analysis Using SAS: A Practical Guide, Second Edition, by Paul D. Allison, is an accessible, data-based introduction to methods of survival analysis. Researchers who want to analyze survival data with SAS will find just what they need with this fully updated new edition that incorporates the many enhancements in SAS procedures for survival analysis in SAS 9. Although the book assumes only a minimal knowledge of SAS, more experienced users will learn new techniques of data input and manipulation. Numerous examples of SAS code and output make this an eminently practical book, ensuring that even the uninitiated become sophisticated users of survival analysis. The main topics presented include censoring, survival curves, Kaplan-Meier estimation, accelerated failure time models, Cox regression models, and discrete-time analysis. Also included are topics not usually covered in survival analysis books, such as time-dependent covariates, competing risks, and repeated events. Survival Analysis Using SAS: A Practical Guide, Second Edition, has been thoroughly updated for SAS 9, and all figures are presented using ODS Graphics. This new edition also documents major enhancements to the STRATA statement in the LIFETEST procedure; includes a section on the PROBPLOT command, which offers graphical methods to evaluate the fit of each parametric regression model; introduces the new BAYES statement for both parametric and Cox models, which allows the user to do a Bayesian analysis using MCMC methods; demonstrates the use of the counting process syntax as an alternative method for handling time-dependent covariates; contains a section on cumulative incidence functions; and describes the use of the new GLIMMIX procedure to estimate random-effects models for discrete-time data. This book is part of the SAS Press program.
Author: David F. Findley
Author: David F. Findley
Author: Wayne A. Fuller
Author: 
Author: American Statistical Association. Survey Research Methods Section
Author: Peter A. Zadrozny
Author: American Statistical Association. Business and Economic Statistics Section
Author: Maxwell L. King
Author: James LeSage
Author: G. Arminger
Author: Paul D. Allison