Download or read book Efficient Estimation of Linear Regression Models with Autocorrelated Errors written by Mathew James Morey and published by . This book was released on 1977 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Relative Error Estimation and Efficient Estimation of Censored Linear Regression Model written by Yuanyuan Lin and published by . This book was released on 2011 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimating the Autocorrelated Error Model with Trended Data Further Results written by Rolla Edward Park and published by . This book was released on 1979 with total page 54 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).

Download or read book Improved Estimation of the Linear Regression Model with Autocorrelated Errors written by A. Chaturvedi and published by . This book was released on 1990 with total page 11 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Regression in Time Series Partial Linear Models written by Peter C. B. Phillips and published by . This book was released on 2002 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Estimation of Regression Parameters in Linear Regression Model with Autocorrelated Errors written by Thuan Van Truong and published by . This book was released on 1980 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation in a Regression Model with Missing Responses written by Scott Daniel Crawford and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: This article examines methods to efficiently estimate the mean response in a linear model with an unknown error distribution under the assumption that the responses are missing at random. We show how the asymptotic variance is affected by the estimator of the regression parameter and by the imputation method. To estimate the regression parameter the Ordinary Least Squares method is efficient only if the error distribution happens to be normal. If the errors are not normal, then we propose a One Step Improvement estimator or a Maximum Empirical Likelihood estimator to estimate the parameter efficiently. In order to investigate the impact that imputation has on estimation of the mean response, we compare the Listwise Deletion method and the Propensity Score method (which do not use imputation at all), and two imputation methods. We show that Listwise Deletion and the Propensity Score method are inefficient. Partial Imputation, where only the missing responses are imputed, is compared to Full Imputation, where both missing and non-missing responses are imputed. Our results show that in general Full Imputation is better than Partial Imputation. However, when the regression parameter is estimated very poorly, then Partial Imputation will outperform Full Imputation. The efficient estimator for the mean response is the Full Imputation estimator that uses an efficient estimator of the parameter.

Download or read book Efficient Estimation in a Generalized Regression Model written by Oscar Tin Go and published by . This book was released on 1989 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation of Linear and Type I Censored Regression Models Under Conditional Quantile Restrictions written by Whitney K. Newey and published by . This book was released on 1987 with total page 33 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Efficient Estimation of Regression Models with User specified Parametric Model for Heteroskedasticty written by Saraswata Chaudhuri and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Semiparametrically Efficient Estimation of the Average Linear Regression Function written by Bryan S. Graham and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Convenient Methods for Estimation of Linear Regression Models with MA 1 Errors written by Glenn M. MacDonald and published by Kingston, Ont. : Institute for Economic Research, Queen's University. This book was released on 1983 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Introduction to Linear Regression Analysis written by Douglas C. Montgomery and published by Wiley-Interscience. This book was released on 2001-04-16 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive and thoroughly up-to-date look at regression analysis-still the most widely used technique in statistics today As basic to statistics as the Pythagorean theorem is to geometry, regression analysis is a statistical technique for investigating and modeling the relationship between variables. With far-reaching applications in almost every field, regression analysis is used in engineering, the physical and chemical sciences, economics, management, life and biological sciences, and the social sciences. Clearly balancing theory with applications, Introduction to Linear Regression Analysis describes conventional uses of the technique, as well as less common ones, placing linear regression in the practical context of today's mathematical and scientific research. Beginning with a general introduction to regression modeling, including typical applications, the book then outlines a host of technical tools that form the linear regression analytical arsenal, including: basic inference procedures and introductory aspects of model adequacy checking; how transformations and weighted least squares can be used to resolve problems of model inadequacy; how to deal with influential observations; and polynomial regression models and their variations. Succeeding chapters include detailed coverage of: ? Indicator variables, making the connection between regression and analysis-of-variance modelss ? Variable selection and model-building techniques ? The multicollinearity problem, including its sources, harmful effects, diagnostics, and remedial measures ? Robust regression techniques, including M-estimators, Least Median of Squares, and S-estimation ? Generalized linear models The book also includes material on regression models with autocorrelated errors, bootstrapping regression estimates, classification and regression trees, and regression model validation. Topics not usually found in a linear regression textbook, such as nonlinear regression and generalized linear models, yet critical to engineering students and professionals, have also been included. The new critical role of the computer in regression analysis is reflected in the book's expanded discussion of regression diagnostics, where major analytical procedures now available in contemporary software packages, such as SAS, Minitab, and S-Plus, are detailed. The Appendix now includes ample background material on the theory of linear models underlying regression analysis. Data sets from the book, extensive problem solutions, and software hints are available on the ftp site. For other Wiley books by Doug Montgomery, visit our website at www.wiley.com/college/montgomery.

Download or read book Linear Regression written by Jürgen Groß and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book covers the basic theory of linear regression models and presents a comprehensive survey of different estimation techniques as alternatives and complements to least squares estimation. Proofs are given for the most relevant results, and the presented methods are illustrated with the help of numerical examples and graphics. Special emphasis is placed on practicability and possible applications. The book is rounded off by an introduction to the basics of decision theory and an appendix on matrix algebra.

Download or read book Estimating the Autocorrelated Error Model with Trended Data written by Rolla Edward Park and published by . This book was released on 1978 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Monte Carlo study is made of the small sample properties of various estimators of the linear regression model with first-order autocorrelated errors. When independent variables are trended, estimators using T transformed observations (Prais-Winsten) are much more efficient than those using T-1 (Cochrane-Orcutt). The best of the feasible estimators is iterated Prais-Winsten using a sum-of-squared-error minimizing estimate of the autocorrelation coefficient rho. None of the feasible estimators performs well in hypothesis testing; all seriously underestimate standard errors, making estimated coefficients appear to be much more significant than they actually are. (Author).

Download or read book Readings in Econometric Theory and Practice written by W.E. Griffiths and published by Elsevier. This book was released on 2014-06-28 with total page 391 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume honors George Judge and his many, varied and outstanding contributions to econometrics, statistics, mathematical programming and spatial equilibrium modeling. The papers are grouped into four parts, each part representing an area in which Professor Judge has made a significant contribution. The authors have all benefited in some way, directly or indirectly, through an association with George Judge and his work. The three papers in Part I are concerned with various aspects of pre-test and Stein-rule estimation. Part II contains applications of Bayesian methodology, new developments in Bayesian methodology, and an overview of Bayesian econometrics. The papers in Part III comprise new developments in time-series analysis, improved estimation and Markov chain analysis. The final part on spatial equilibrium modeling contains papers that had their origins from Professor Judge's pioneering work in the 60's.

Download or read book Efficient Estimation and Testing of Regressions with a Serially Correlated Error Component written by Maxwell L. King and published by . This book was released on 1986 with total page 21 pages. Available in PDF, EPUB and Kindle. Book excerpt: