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Asymptotic Behaviour Of Weighted Least Squares Estimator In Linear Functional Error In Variables Models
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Author :Carleton University. Laboratory for Research in Statistics and Probability Publisher : ISBN 13 : Total Pages :16 pages Book Rating :4.:/5 (58 download)
Book Synopsis Asymptotic Behaviour of Weighted Least Squares Estimator in Linear Functional Error-in-variables Models by : Carleton University. Laboratory for Research in Statistics and Probability
Download or read book Asymptotic Behaviour of Weighted Least Squares Estimator in Linear Functional Error-in-variables Models written by Carleton University. Laboratory for Research in Statistics and Probability and published by . This book was released on 2001 with total page 16 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory by : Hira Koul
Download or read book Asymptotic Distribution of the Bias Corrected Least Squares Estimators in Measurement Error Linear Regression Models Under Long Memory written by Hira Koul and published by . This book was released on 2020 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This article derives the consistency and asymptotic distribution of the bias corrected least squares estimators (LSEs) of the regression parameters in linear regression models when covariates have measurement error (ME) and errors and covariates form mutually independent long memory moving average processes. In the structural ME linear regression model, the nature of the asymptotic distribution of suitably standardized bias corrected LSEs depends on the range of the values of where ,, and are the LM parameters of the covariate, ME and regression error processes respectively. This limiting distribution is Gaussian when and non-Gaussian in the case . In the former case some consistent estimators of the asymptotic variances of these estimators and a log()-consistent estimator of an underlying LM parameter are also provided. They are useful in the construction of the large sample confidence intervals for regression parameters. The article also discusses the asymptotic distribution of these estimators in some functional ME linear regression models, where the unobservable covariate is non-random. In these models, the limiting distribution of the bias corrected LSEs is always a Gaussian distribution determined by the range of the values of )-)
Book Synopsis Consistency and Inconsistency of the Weighted Least Squares Estimator in Linear Functional Relations with Dependent Error Terms by : Alexander Kukush
Download or read book Consistency and Inconsistency of the Weighted Least Squares Estimator in Linear Functional Relations with Dependent Error Terms written by Alexander Kukush and published by . This book was released on 1997 with total page 9 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Comparisons Between Some Estimators in Functional Errors-in-Variables Regression Models by : Raymond J. Carroll
Download or read book Comparisons Between Some Estimators in Functional Errors-in-Variables Regression Models written by Raymond J. Carroll and published by . This book was released on 198? with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: This report studies the functional errors-in-variables regression model. In the case of no equation error (all randomness due to measurement errors), the maximum likelihood estimator computed assuming normality is asymptotically better than the usual moments estimator, even if the errors are not normally distributed. For certain statistical problems such as randomized two group analysis of covariance, the least squares estimate is shown to be better than the aformentioned errors-in-variables methods for estimating certain important contrasts.
Book Synopsis Estimating Weights in Heteroscedastic Regression Models by Applying Least Squares to Squared Or Absolute Residuals by : Raymond J. Carroll
Download or read book Estimating Weights in Heteroscedastic Regression Models by Applying Least Squares to Squared Or Absolute Residuals written by Raymond J. Carroll and published by . This book was released on 1985 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document considers a nonlinear regression model for which the variances depend on a parametric function of known variables. The authors focus on estimating the variance function, after what it is typical to estimate the mean function by weighted least squares. Most often, squared residuals from an unweighted least squares fit are compared to their expectations and used to estimate the variance function. If properly weighted such methods are asymptotically equivalent to normal-theory maximum likelihood. Instead, one could use the deviations of the absolute residuals from their expectations. Constructed is such an estimator of the variance function based on absolute residuals whose asymptotic efficiency relative to maximum likelihood is precisely the same for symmetric errors as the asymptotic efficiency in the one-sample problem of the mean absolute deviation relative to the sample variance. The estimators are computable using nonlinear least squares software. The results hold with minimal distributional assumptions. (Author).
Book Synopsis Econometrics in Theory and Practice by : Robert Galata
Download or read book Econometrics in Theory and Practice written by Robert Galata and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: 9
Book Synopsis Nonparametric Estimation of Weights in Least-squares Regression Analysis by :
Download or read book Nonparametric Estimation of Weights in Least-squares Regression Analysis written by and published by . This book was released on 1978 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Resurrecting Weighted Least Squares by : Joseph P. Romano
Download or read book Resurrecting Weighted Least Squares written by Joseph P. Romano and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Asymptotic Properties in Space and Time of an Estimator in Non-linear Functional Errors-in-variables Model by : István Fazekas
Download or read book Asymptotic Properties in Space and Time of an Estimator in Non-linear Functional Errors-in-variables Model written by István Fazekas and published by . This book was released on 1998 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Partially Linear Models by : Wolfgang Härdle
Download or read book Partially Linear Models written by Wolfgang Härdle and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics. Many methods and techniques have been proposed and studied. This monograph hopes to bring an up-to-date presentation of the state of the art of partially linear regression techniques. The emphasis is on methodologies rather than on the theory, with a particular focus on applications of partially linear regression techniques to various statistical problems. These problems include least squares regression, asymptotically efficient estimation, bootstrap resampling, censored data analysis, linear measurement error models, nonlinear measurement models, nonlinear and nonparametric time series models.
Book Synopsis An Asymptotic Theory for Weighted Least Squares with Weights Estimated by Replication by : Raymond J. Carroll
Download or read book An Asymptotic Theory for Weighted Least Squares with Weights Estimated by Replication written by Raymond J. Carroll and published by . This book was released on 1988 with total page 19 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document considers a heteroscedastic linear regression model with replication. To estimate the variances, one can use the sample variances or the sample average squared errors from a regression fit. The authors study the large sample properties of these weighted least squares estimates with estimated weights when the number of replicates is small. The estimates are generally inconsistent for asymmetrically distributed data. If sample variances are used based on m replicates, the weighted least squares estimates are inconsistent for m=2 replicates even when the data are normally distributed. With between 3 and 5 replicates, the rates of convergence are slower than the usual square root of N. With m> or = 6 replicates, the effect of estimating the weights is to increase variances by (m-5)/(m-3), relative to weighted least squares estimates with known weights. (KR).
Book Synopsis A Note on Amemiya's Form of the Weighted Least Squares Estimator by : Roger Koenker
Download or read book A Note on Amemiya's Form of the Weighted Least Squares Estimator written by Roger Koenker and published by . This book was released on 1992 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Study of the Asymptotic Properties of Lasso Estimates for Correlated Data by : Shuva Gupta
Download or read book A Study of the Asymptotic Properties of Lasso Estimates for Correlated Data written by Shuva Gupta and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ABSTRACT: In this thesis we investigate post-model selection properties of L1 penalized weighted least squares estimators in regression models with a large number of variables M and correlated errors. We focus on correct subset selection and on the asymptotic distribution of the penalized estimators. In the simple case of AR(1) errors we give conditions under which correct subset selection can be achieved via our procedure. We then provide a detailed generalization of this result to models with errors that have a weak-dependency structure (Doukhan 1996). In all cases, the number M of regression variables is allowed to exceed the sample size n. We further investigate the asymptotic distribution of our estimates, when M
Book Synopsis Linear Regression Analysis by : Xin Yan
Download or read book Linear Regression Analysis written by Xin Yan and published by World Scientific. This book was released on 2009 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This volume presents in detail the fundamental theories of linear regression analysis and diagnosis, as well as the relevant statistical computing techniques so that readers are able to actually model the data using the techniques described in the book. This book is suitable for graduate students who are either majoring in statistics/biostatistics or using linear regression analysis substantially in their subject area." --Book Jacket.
Book Synopsis Iterative Weighted Least Squares Estimators in Heteroscedastic Linear Models with Asymmetric Error Distribution by : Qiuhua Jill Jiang
Download or read book Iterative Weighted Least Squares Estimators in Heteroscedastic Linear Models with Asymmetric Error Distribution written by Qiuhua Jill Jiang and published by . This book was released on 1994 with total page 76 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book NBS Special Publication written by and published by . This book was released on 1970 with total page 574 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Penalized M-estimation for Partly Linear Transformation Models with Current Status Data by : Shuangge Ma
Download or read book Penalized M-estimation for Partly Linear Transformation Models with Current Status Data written by Shuangge Ma and published by . This book was released on 2004 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt:
