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Monday, August 10, 2020 | History

4 edition of The statistical implications of pre-test and Stein-rule estimators in econometrics found in the catalog.

The statistical implications of pre-test and Stein-rule estimators in econometrics

George G. Judge

The statistical implications of pre-test and Stein-rule estimators in econometrics

by George G. Judge

  • 294 Want to read
  • 3 Currently reading

Published by North-Holland Pub. Co., sole distributors for the U.S.A. and Canada, Elsevier North-Holland in Amsterdam, New York, New York .
Written in English

    Subjects:
  • Econometrics.,
  • Estimation theory.,
  • Monte Carlo method.

  • Edition Notes

    StatementGeorge G. Judge, M. E. Bock.
    SeriesStudies in mathematical and managerial economics ;, v. 25
    ContributionsBock, M. E.
    Classifications
    LC ClassificationsHB139 .J8
    The Physical Object
    Paginationxvi, 340 p. :
    Number of Pages340
    ID Numbers
    Open LibraryOL4553080M
    ISBN 10072040729X
    LC Control Number77022603

    The Statistical Implications of Pre-Test and Stein- Rule Estimators in Econometrics, (). Theory of Preliminary Test and Stein-Type Estimation with Applications, Wiley ShalabhAuthor: Shalabh Shalabh and Christian Heumann. Namba, Akio & Ohtani, Kazuhiro, "PMSE performance of the Stein-rule and positive-part Stein-rule estimators in a regression model with or without proxy variables," Statistics & Probability Letters, Elsevier, vol. 76(9), pages , May. Ohtani, Kazuhiro,

      The exact density and distribution functions of the inequality constrained and pre-test estimators The exact density and distribution functions of the inequality constrained and pre-test estimators Wan, Alan We consider a bivariate normal linear regression model with an inequality restriction imposed on one of the regression coefficients. hood estimation methods for Gaussian models, in common use for more than a century, were inadmissible beyond simple one- or two-dimensional situations. These methods are still in use, for good reasons, but Stein-type estimators have pointed the way toward a radically di erent empirical Bayes approach to high-dimensional statistical Size: KB.

    This book supplements econometrics texts, at all levels, by providing an overview of the subject and an intuitive feel for its concepts and techniques, without the usual clutter of notation and technical detail that necessarily characterize an econometrics textbook. It is often said of econometrics textbooks that their readers miss the forest File Size: KB. The statistical implications of pre-test and Stein-rule estimators in econometrics (Studies in mathematical and managerial economics Volume 25) George G. Judge Out of Stock.


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The statistical implications of pre-test and Stein-rule estimators in econometrics by George G. Judge Download PDF EPUB FB2

The statistical implications of pre-test and Stein-rule estimators in econometrics (Studies in mathematical and managerial economics Volume 25) [George G. Judge, M. Bock] on *FREE* shipping on qualifying offers. The statistical implications of pre-test and Stein-rule estimators in econometrics (Studies in mathematical and managerial economics Volume 25)Cited by:   ().

The Statistical Implications of Pre-Test and Stein-Rule Estimators in Econometrics. Technometrics: Vol. 21, No. 3, pp. Cited by: The Statistical Implications of Pre‐test and Stein‐rule Estimators in Econometrics. By George G. Judge and M. Bock. Amsterdam, North‐Holland, xvi. The statistical implications of pre-test and Stein-rule estimators in econometrics.

[George G Judge; M E Bock] and tests --Preliminary test estimator for the orthonormal statistical model --The Stein-rule estimators --Some Monte Carlo sampling results, identity covariance. The Statistical Implications of Pre-Test and Stein-Rule Estimators in Econometrics Article in Technometrics 21(3) April with 39 Reads How we measure 'reads'.

Judge, G.G. and M.E. Bock,The statistical implications of pre-test and Stein-rule estimators in econometrics (North-Holland, Amsterdam). Nakamura, A. and M. Nakamura,On the relationships among several specification error tests presented by Durbin, Wu, and Hausman, Econometrica, Cited by: 6.

Judge and M. Bock, “The Statistical Implications of Pre-Test and Stein-Rule Estimators in Econometrics,” North Holland, New York, P. Wijekoon, “Mixed Estimation and Preliminary Test Estimation in the Linear Regression Model,” PhD Thesis, University of Dortmund, Dortmund, Cited by: 7.

A consequence of the above discussion is the following counterintuitive result: When three or more unrelated parameters are measured, their total MSE can be reduced by using a combined estimator such as the James–Stein estimator; whereas when each parameter is estimated separately, the least squares (LS) estimator is admissible.

A quirky example would be estimating the speed of light, tea. Judge, G.G. & Bock, M.E. () The Statistical Implications of Pre-Test and Stein Rule Estimators in Econometrics.

North-Holland. Kabaila, P. () The effect of model selection on confidence regions and prediction by: This paper explores by means of a Monte Carlo experiment the consequences of autocorrelation pre-testing on estimation, hypothesis testing and prediction in the linear regression model with first-order autoregressive by: Pre-test Estimation and Testing in Econometrics: Recent Developments.

Article (PDF Available) in Journal of Economic Surveys 7(2) February with 2, Reads How we measure 'reads'. When different estimators are available, preliminary test estimation procedure is adopted to select a suitable estimator.

In this paper, two ridge estimators, the Stochastic Restricted Liu Estimator and Liu Estimator are combined to define a new preliminary test estimator, namely the Preliminary Test Stochastic Restricted Liu Estimator (PTSRLE). The Statistical Implications of Pre-Test and Stein-Rule Estimators in Econometrics by George G.

Judge, M. Bock (pp. ) Review by: Rand R. Wilcox DOI: / Econometrics | Chapter 14 | Stein-Rule Estimation | Shalabh, IIT Kanpur 6 Since c 0 is assumed, so this inequality holds true when 22 0 kc or ck provided k 2. So as long as ck is satisfied, the Stein-rule estimator will have smaller predictive risk them OLSE.

This inequality is not satisfied for 1k and 2.k. Recursions for the Moments of Some Continuous Distributions The Statistical Implications of Pre-Test and Stein-Rule Estimators in GMM Goodness of fit gr Grad. students Granger causality Graphs Gretl H-P filter Heteroskadasticity Heteroskedasticity History of econometrics History of statistics Humour Hypothesis testing Identification.

The statistical implications of pre-test and Stein-rule estimators in econometrics: 2. The Statistical Implications of Pre-test and Stein-rule Estimators in Econometrics.

North-Holland, Amsterdam. Kempthorne, Controlling risks under different loss functions: The compromise decision problem. Annals of Statistics. v Khan and Ahmed, Cited by: All journal articles featured in Technometrics vol 21 issue 3. Cart. The online home for the publications of the American Statistical Association.

Impact Factor. Technometrics. Search in: Submit an article The Statistical Implications of Pre-Test and Stein-Rule Estimators in Econometrics.

Rand R. Wilcox. Pages: Ohtani, Kazuhiro Testing the disturbance variance after a pre-test for a linear hypothesis on coefficients in a linear ications in Statistics - Cited by:   1 Introduction. Econometrics is concerned with the application of statistical methods to economic data.

Economists often apply statistical methods to data in order to quantify or test their theories or to make forecasts (See Forecasting).However, traditional statistical methods are not always appropriate for application to economic data, in the sense that the assumptions underlying these.

The Conventional Statistical Model and Estimator Base. In econometrics the most widely used estimation and inference techniques are based on linear statistical models and maximum likelihood (ML) and least squares concepts.The text is extremely student friendly, with pathways designed for semester usage, and although aimed primarily at students at second-year undergraduate level and above studying econometrics and economics, Probability Theory and Statistical Inference will also be useful for students in other disciplines that make extensive use of observational Cited by: Carter, R.

A. L., "Improved Stein-rule estimator for regression problems," Journal of Econometrics, Elsevier, vol. 17(1), pages, Kazuhiro, "Optimal levels of significance of a pre-test in estimating the disturbance variance after the pre-test for a linear hypothesis on coefficients in a linear regression," Economics Letters, Elsevier, vol.

28(2), pages