Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Estimation Of Regression Parameters In Linear Regression Model With Autocorrelated Errors PDF full book. Access full book title Estimation Of Regression Parameters In Linear Regression Model With Autocorrelated Errors.
| Author | : Thuan Van Truong |
| Publisher | : |
| Total Pages | : 218 |
| Release | : 1980 |
| Genre | : Autocorrelation (Statistics) |
| ISBN | : |
| Author | : Thuan V. Truong |
| Publisher | : |
| Total Pages | : 109 |
| Release | : 1983 |
| Genre | : |
| ISBN | : |
| Author | : A. Chaturvedi |
| Publisher | : |
| Total Pages | : 11 |
| Release | : 1990 |
| Genre | : Estimation theory |
| ISBN | : 9780864181619 |
| Author | : Jürgen Groß |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 400 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 364255864X |
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.
| Author | : Maxwell L. King |
| Publisher | : Routledge |
| Total Pages | : 550 |
| Release | : 2018-03-05 |
| Genre | : Business & Economics |
| ISBN | : 1351140663 |
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 | : Pavel S. Knopov |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 245 |
| Release | : 2011-09-28 |
| Genre | : Business & Economics |
| ISBN | : 1461405742 |
This monograph focuses on the construction of regression models with linear and non-linear constrain inequalities from the theoretical point of view. Unlike previous publications, this volume analyses the properties of regression with inequality constrains, investigating the flexibility of inequality constrains and their ability to adapt in the presence of additional a priori information The implementation of inequality constrains improves the accuracy of models, and decreases the likelihood of errors. Based on the obtained theoretical results, a computational technique for estimation and prognostication problems is suggested. This approach lends itself to numerous applications in various practical problems, several of which are discussed in detail The book is useful resource for graduate students, PhD students, as well as for researchers who specialize in applied statistics and optimization. This book may also be useful to specialists in other branches of applied mathematics, technology, econometrics and finance
| Author | : |
| Publisher | : IICA |
| Total Pages | : 122 |
| Release | : |
| Genre | : |
| ISBN | : |
| Author | : Rachel T. Silvestrini |
| Publisher | : Quality Press |
| Total Pages | : 468 |
| Release | : 2018-04-26 |
| Genre | : Education |
| ISBN | : 0873899695 |
This comprehensive but low-cost textbook is intended for use in an undergraduate level regression course, as well as for use by practitioners. The authors have included some statistical details throughout the book but focus on interpreting results for real applications of regression analysis. Chapters are devoted to data collection and cleaning; data visualization; model fitting and inference; model prediction and inference; model diagnostics; remedial measures; model selection techniques; model validation; and a case study demonstrating the techniques outlined throughout the book. The examples throughout each chapter are illustrated using the software packages R and JMP. At the end of each chapter, there is a tutorial section demonstrating the use of both R and JMP. The R tutorial contains source code and the JMP tutorial contains a step by step guide. Each chapter also includes exercises for further study and learning.
| Author | : 方偉泉 |
| Publisher | : |
| Total Pages | : |
| Release | : 2015 |
| Genre | : |
| ISBN | : |
| Author | : K. Sreenivasulu |
| Publisher | : LAP Lambert Academic Publishing |
| Total Pages | : 268 |
| Release | : 2013 |
| Genre | : |
| ISBN | : 9783659389726 |
In this some new estimation methods and testing procedures for the linear regression models with heteroscedastic disturbances. A Minimum Norm Quadratic Unbiased (MINQU) estimation method has been developed for estimating the unknown heteroscedastic error variances by using the weighted studentized residuals. A multiplicative heteroscedastic linear regression model has been specified and a method of estimating the parameters of linear regression model along with the in the heteroscedastic error variance has been given by using the predicted residuals. Three types of modified estimators have been proposed for the parameter of multiplicative heteroscedastic error variance by using internally studentized residuals.an adaptive method of estimation has been suggested to estimate the heteroscedastic error variances based on Bartlett's test by using the internally studentized residuals. Besides these new estimation methods, the testing procedures for testing the equality between the regression coefficients in two/sets of linear regression models under heteroscedasticity have been suggested by using the studentized residuals.
