A Note on the Estimation of Linear Regression Models with Heteroskedastic Measurement Errors PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Note on the Estimation of Linear Regression Models with Heteroskedastic Measurement Errors PDF full book. Access full book title A Note on the Estimation of Linear Regression Models with Heteroskedastic Measurement Errors by Daniel Gerard Sullivan. Download full books in PDF and EPUB format.
Author: Daniel Gerard Sullivan
Publisher:
ISBN:
Category : Regression analysis
Languages : en
Pages : 44
Get Book Here
Book Description
Author: Daniel Gerard Sullivan
Publisher:
ISBN:
Category : Regression analysis
Languages : en
Pages : 44
Get Book Here
Book Description
Author: Constantin Colonescu
Publisher: Lulu.com
ISBN: 1387473611
Category : Business & Economics
Languages : en
Pages : 278
Get Book Here
Book Description
This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.
Author: Humberto Barreto
Publisher: Cambridge University Press
ISBN: 9780521843195
Category : Business & Economics
Languages : en
Pages : 810
Get Book Here
Book Description
This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.
Author: Sanford Weisberg
Publisher: John Wiley & Sons
ISBN: 1118625951
Category : Mathematics
Languages : en
Pages : 266
Get Book Here
Book Description
Master linear regression techniques with a new edition of a classic text Reviews of the Second Edition: "I found it enjoyable reading and so full of interesting material that even the well-informed reader will probably find something new . . . a necessity for all of those who do linear regression." —Technometrics, February 1987 "Overall, I feel that the book is a valuable addition to the now considerable list of texts on applied linear regression. It should be a strong contender as the leading text for a first serious course in regression analysis." —American Scientist, May–June 1987 Applied Linear Regression, Third Edition has been thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. To facilitate quick learning, the Third Edition stresses the use of graphical methods in an effort to find appropriate models and to better understand them. In that spirit, most analyses and homework problems use graphs for the discovery of structure as well as for the summarization of results. The Third Edition incorporates new material reflecting the latest advances, including: Use of smoothers to summarize a scatterplot Box-Cox and graphical methods for selecting transformations Use of the delta method for inference about complex combinations of parameters Computationally intensive methods and simulation, including the bootstrap method Expanded chapters on nonlinear and logistic regression Completely revised chapters on multiple regression, diagnostics, and generalizations of regression Readers will also find helpful pedagogical tools and learning aids, including: More than 100 exercises, most based on interesting real-world data Web primers demonstrating how to use standard statistical packages, including R, S-Plus®, SPSS®, SAS®, and JMP®, to work all the examples and exercises in the text A free online library for R and S-Plus that makes the methods discussed in the book easy to use With its focus on graphical methods and analysis, coupled with many practical examples and exercises, this is an excellent textbook for upper-level undergraduates and graduate students, who will quickly learn how to use linear regression analysis techniques to solve and gain insight into real-life problems.
Author: Christian Kleiber
Publisher: Springer Science & Business Media
ISBN: 0387773185
Category : Business & Economics
Languages : en
Pages : 229
Get Book Here
Book Description
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.
Author: Larry D. Schroeder
Publisher: SAGE Publications
ISBN: 1506361617
Category : Social Science
Languages : en
Pages : 122
Get Book Here
Book Description
Understanding Regression Analysis: An Introductory Guide by Larry D. Schroeder, David L. Sjoquist, and Paula E. Stephan presents the fundamentals of regression analysis, from its meaning to uses, in a concise, easy-to-read, and non-technical style. It illustrates how regression coefficients are estimated, interpreted, and used in a variety of settings within the social sciences, business, law, and public policy. Packed with applied examples and using few equations, the book walks readers through elementary material using a verbal, intuitive interpretation of regression coefficients, associated statistics, and hypothesis tests. The Second Edition features updated examples and new references to modern software output.
Author: Samuel Bowles
Publisher: Princeton University Press
ISBN: 1400835496
Category : Social Science
Languages : en
Pages : 315
Get Book Here
Book Description
Is the United States "the land of equal opportunity" or is the playing field tilted in favor of those whose parents are wealthy, well educated, and white? If family background is important in getting ahead, why? And if the processes that transmit economic status from parent to child are unfair, could public policy address the problem? Unequal Chances provides new answers to these questions by leading economists, sociologists, biologists, behavioral geneticists, and philosophers. New estimates show that intergenerational inequality in the United States is far greater than was previously thought. Moreover, while the inheritance of wealth and the better schooling typically enjoyed by the children of the well-to-do contribute to this process, these two standard explanations fail to explain the extent of intergenerational status transmission. The genetic inheritance of IQ is even less important. Instead, parent-offspring similarities in personality and behavior may play an important role. Race contributes to the process, and the intergenerational mobility patterns of African Americans and European Americans differ substantially. Following the editors' introduction are chapters by Greg Duncan, Ariel Kalil, Susan E. Mayer, Robin Tepper, and Monique R. Payne; Bhashkar Mazumder; David J. Harding, Christopher Jencks, Leonard M. Lopoo, and Susan E. Mayer; Anders Björklund, Markus Jäntti, and Gary Solon; Tom Hertz; John C. Loehlin; Melissa Osborne Groves; Marcus W. Feldman, Shuzhuo Li, Nan Li, Shripad Tuljapurkar, and Xiaoyi Jin; and Adam Swift.
Author: Raymond J. Carroll
Publisher: Routledge
ISBN: 1351407279
Category : Mathematics
Languages : en
Pages : 264
Get Book Here
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: Aman Ullah
Publisher: CRC Press
ISBN: 1482269902
Category : Business & Economics
Languages : en
Pages : 646
Get Book Here
Book Description
This work examines theoretical issues, as well as practical developments in statistical inference related to econometric models and analysis. This work offers discussions on such areas as the function of statistics in aggregation, income inequality, poverty, health, spatial econometrics, panel and survey data, bootstrapping and time series.
Author: Jeffrey M. Wooldridge
Publisher: MIT Press
ISBN: 0262232588
Category : Business & Economics
Languages : en
Pages : 1095
Get Book Here
Book Description
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.
