Gauss-Newton, Milliken-Graybill, and Exact Misspecification Testing Using Artificial Regressions
The 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.
|Date of creation:||30 Nov 1998|
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- Russell Davidson & James G. MacKinnon, 1999.
978, Queen's University, Department of Economics.
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- Godfrey, Leslie G & McAleer, Michael & McKenzie, Colin R, 1988. "Variable Addition and LaGrange Multiplier Tests for Linear and Logarithmic Regression Models," The Review of Economics and Statistics, MIT Press, vol. 70(3), pages 492-503, August.
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- Russell Davidson & James G. MacKinnon, 1981. "Small Sample Properties of Alternative Forms of the Lagrange Multiplier Test," Working Papers 439, Queen's University, Department of Economics.
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