Gauss-Newton, Milliken-Graybill, and Exact Misspecification Testing Using Artificial Regressions
AbstractThe Gauss-Newton regression (GNR) is widely used to compute Lagrange multiplier statistics. A regression described by Milliken and Graybill yields an exact F test in a certain class of nonlinear models which are linear under the null. This paper shows that the Milliken- Graybill regression is a GNR. Hence one interpretation of Milliken- Graybill is that they identi ed a class of nonlinear models for which the GNR yields an exact test.
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Bibliographic InfoPaper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 9811.
Length: 9 pages
Date of creation: 30 Nov 1998
Date of revision:
Note: ISSN 1485-6441
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Specification testing; Milliken-Graybill Theorem; Gauss- Newton regression;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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Blog mentionsAs found by EconAcademics.org, the blog aggregator for Economics research:
- The Milliken-Graybill Theorem
by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2012-07-06 15:08:00
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