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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

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

Classifications The Physical Object Statement George G. Judge, M. E. Bock. Series Studies in mathematical and managerial economics ;, v. 25 Contributions Bock, M. E. LC Classifications HB139 .J8 Pagination xvi, 340 p. : Number of Pages 340 Open Library OL4553080M ISBN 10 072040729X LC Control Number 77022603

Econometrics, mathematical economics, statistics, intermediate and advanced economic theory, spatial economics, mathematical programming, decision problems under uncertainty. Research. Specification and evaluation of the sampling performance of alternative linear and nonlinear statistical decision rules. Improved methods of inference. A Small Sampling of Readings and Background Papers: Econometric Theory Akaike, Hirotuku, , Information theory and an extension of the maximum likelihood prin- Judge, G. and M.E. Bock, , The Statistical Implications of Pre-test and Stein-rule Estima-tors in Econometrics S., J. Hodges, S.J. Press and A. Zellner (Eds.), Bayesian File Size: KB. Econometrics; Econometrics Project; Need an expert in econometrics. Budget- 30$I have Masters degree in Economics and Statistics. I also have years of professional experience working as a Quantitative Analyst (in the field of Statistics). matching estimators on the provided data ($ AUD) Search Engine Marketing (\$ USD.

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

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 The estimation of the regression parameters for the ill-conditioned logistic regression model is considered in this paper. We proposed five ridge regression (RR) estimators, namely, unrestricted RR, restricted ridge regression, preliminary test RR, shrinkage ridge regression and positive rule RR estimators for estimating the parameters $$(\beta)$$ when it is suspected that the parameter Cited by: The Methodology and Practice of Econometrics: A Festschrift in Honour of David F.

Hendry, Oxford University Press, Oxford, forthcoming. Judge, G. G., and M. Bock () The Statistical Implications of Pre-test and Stein-rule Estimators in Econometrics, North-Holland, Amsterdam. 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), pagesMay. 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. George G. Judge. Professor Emeritus. Research Description: (), Pre-Test and Stein-Rule Estimators: Some New Results, Amsterdam: North-Holland Publishing Co., pages. The Statistical Implications of Pre-test and Stein-rule Estimators in Econometrics, Amsterdam: North-Holland Publishing Co., pages.

Second Edition Ridge Regression and Stein Rule Estimators e. Non-Linear Models f. Model Choice g. Rational Expectations Models RESTAT = Review of Economics and Statistics; RESTUD = Review of Economic Studies. Topic numbers correspond to those in the course outline.

Implications of Pre-Test and Stein-Rule Estimators in Econometrics, North Holland, In orthogonal frequency division multiple access-based systems where channel frequency response (CFR) estimation has to be carried out using only the user-specific (localised) pilots within a small time frequency block, the accuracy of the estimates suffer because of the limited number of pilots and imperfect knowledge of the channel : Sheetal Kalyani, Raghavendran Lakshminarayanan, Krishnamurthy Giridhar.

Journal of the Royal Statistical Society. Series A (General), Vol.No. 4, Judge, G. & M. Bock (): The Statistical Implications of Pre-test and Stein-Rule Estimators in Econometrics.

North-Holland. Leeb, H. & B. Pötscher (): The finite-sample distribution of post-model-selection estimators and uniform versus nonuniform approximations. (Organized the Interdisciplinary Statistics Group) Served on various departmental committees (e.g., computer accounts, awards, chair search) Scienti c misconduct committee ().

BOOK REVIEWS The statistical implications of pre-test and Stein-rule estimators in econometrics. By G. Judge & M. Bock Technometrics,21, File Size: KB. Offering students a unifying theoretical perspective, this innovative text emphasizes nonlinear techniques of estimation, including nonlinear least squares, nonlinear instrumental variables, maximum likelihood and the generalized method of moments, but nevertheless relies heavily on simplegeometrical arguments to develop intuition.

One theme of the book is the use of artificial regressions for. Optimal pre-test estimators in regression Optimal pre-test estimators in regression Reif, Jiři; Vlček, Karel Pre-testing in a linear regression model is studied with general measurable sets as ‘regions of significance’ for the usual test statistic t associated with the estimate of a given regression coefficient.

Model Validation in Spatial Econometrics: A Review and Evaluation of Alternative Approaches Show all authors In Studies in Bayesian econometrics and statistics in honor of Leonard J.

Savage, eds. Fienberg and A The statistical implications of pre-test and Stein-Rule estimators in econometrics. Amsterdam: North Holland.

Google Cited by:. Judge GG, Bock ME pdf The statistical implications of pre-test and Stein-rule estimators in econometrics. Elsevier, North-Holland Judge GG, Yancey TA () Improved methods of inference in : Akio Namba.In this paper, we consider an estimation problem of the regression coefficients download pdf multiple regression models with several unknown change-points.

Under some realistic assumptions, we propose a class of estimators which includes as a special cases shrinkage estimators (SEs) as well as the unrestricted estimator (UE) and the restricted estimator.b1 and b2 are efficient ebook that is, the variance of each estimator is less than the variance of any of the linear unbiased estimator.

t test Degrees of freedom: This test has a distribution t with n-2 degrees of freedom.