Consistent Estimation In Linear Regression With Errors In Variables PDF Download
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Author | : Leif Nilsson |
Publisher | : |
Total Pages | : 17 |
Release | : 1998 |
Genre | : |
ISBN | : |
Download Consistent Estimation in Linear Regression with Errors in Variables Book in PDF, ePub and Kindle
Author | : Lung-Fei Lee |
Publisher | : |
Total Pages | : 28 |
Release | : 1992 |
Genre | : Estimation theory |
ISBN | : |
Download Consistent Estimation of Linear and Nonlinear Errors-in- Variables Models with Validation Information Book in PDF, ePub and Kindle
Author | : Lung-Fei Lee |
Publisher | : |
Total Pages | : 0 |
Release | : 1992 |
Genre | : Estimation theory |
ISBN | : |
Download Consistent Estimation of Linear and Nonlinear Errors-in- Variables Models with Validation Information Book in PDF, ePub and Kindle
Author | : Bo Jonsson |
Publisher | : |
Total Pages | : 42 |
Release | : 1992 |
Genre | : Regression analysis |
ISBN | : |
Download Prediction with a Linear Regression Model and Errors in a Regressor Book in PDF, ePub and Kindle
Author | : München Schneeweis |
Publisher | : |
Total Pages | : 16 |
Release | : 1976 |
Genre | : |
ISBN | : |
Download Consistent Estimation of a Regression with Errors in the Variables Book in PDF, ePub and Kindle
Author | : John P. Buonaccorsi |
Publisher | : CRC Press |
Total Pages | : 465 |
Release | : 2010-03-02 |
Genre | : Mathematics |
ISBN | : 1420066587 |
Download Measurement Error Book in PDF, ePub and Kindle
Over the last 20 years, comprehensive strategies for treating measurement error in complex models and accounting for the use of extra data to estimate measurement error parameters have emerged. Focusing on both established and novel approaches, Measurement Error: Models, Methods, and Applications provides an overview of the main techniques and illu
Author | : Yuehua Wu |
Publisher | : |
Total Pages | : 27 |
Release | : 1987 |
Genre | : |
ISBN | : |
Download Strong Consistency of Estimation of Number of Regression Variables when the Errors are Independent and Their Expectations are Not Equal to Each Other Book in PDF, ePub and Kindle
This document considers the linear regression model y sub i = x sub i B + e sub i, i = 1, 2 ..., where (x sub i) - is a sequence of known p-vectors, Beta = (Beta Sub 1 ..., Beta Sub p) is an unknown p-vector, known as regression coefficients, (e Sub i) is a sequence of random errors. It is of interest to test the hypothesis H Sub k: Beta Sub k+1 = ... = Beta Sub p = O, k = O, 1, ..., p. We do not assume that the random errors are identically distributed and have zero means, since it is sometimes realistic. As a compensation for this relaxation, we assume the errors have a common bounded support A Sub 1, a Sub 2 under certain conditions, we obtain the strongly consistent estimate of the number k for which Beta Sub k is not equal to O and Beta Sub k+1 = ... = Beta Sub p = O, by using the information theoretical criteria.
Author | : Glenn M. MacDonald |
Publisher | : Kingston, Ont. : Institute for Economic Research, Queen's University |
Total Pages | : 36 |
Release | : 1983 |
Genre | : Estimation theory |
ISBN | : |
Download Convenient Methods for Estimation of Linear Regression Models with MA(1) Errors Book in PDF, ePub and Kindle
Author | : Juan Carlos Escanciano |
Publisher | : |
Total Pages | : 28 |
Release | : 2016 |
Genre | : |
ISBN | : |
Download Uniformly Consistent Estimation of Linear Regression Models with Strictly Exogenous Instruments Book in PDF, ePub and Kindle
This paper investigates estimation of linear regression models with strictly exogenous instruments under minimal identifying assumptions. Commonly used Instrumental Variables (IV) estimators are not uniformly consistent in this setting (uniformity is in the underlying data generating process). This negative result is just one way to formalize the well-documented fact of high sensitivity of IV to the presence of weak instruments. This paper introduces a uniformly consistent estimator under nearly the minimal identifying assumption. The proposed estimator, called the Integrated Instrumental Variables (IIV) estimator, is a weighted least squares estimator with trivial implementation. Monte Carlo evidence supports the theoretical claims and suggests that the IIV estimator is a robust alternative to IV and optimal IV in finite samples under weak identification and strictly exogenous instruments. In an application with quarterly UK data IIV estimates a positive and significant elasticity of intertemporal substitution and an equally sensible estimate for its reciprocal, in contrast to IV methods that fail to identify these parameters.
Author | : Raymond J. Carroll |
Publisher | : CRC Press |
Total Pages | : 334 |
Release | : 1995-07-06 |
Genre | : Mathematics |
ISBN | : 9780412047213 |
Download Measurement Error in Nonlinear Models Book in PDF, ePub and Kindle
This monograph provides an up-to-date discussion of analysis strategies for regression problems in which predictor variables are measured with errors. The analysis of nonlinear regression models includes generalized linear models, transform-both-sides models and quasilikelihood and variance function problems. The text concentrates on the general ideas and strategies of estimation and inference rather than being concerned with a specific problem. Measurement error occurs in many fields, such as biometry, epidemiology and economics. In particular, the book contains a large number of epidemiological examples. An outline of strategies for handling progressively more difficult problems is also provided.