Deriving Tests of the Semi-Linear Regression Model Using the Density Function of a Maximal Invariant

Jahar L. Bhowmik () and Maxwell King

No 19/05, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics

Abstract: In the context of a general regression model in which some regression coefficients are of interest and others are purely nuisance parameters, we derive the density function of a maximal invariant statistic with the aim of testing for the inclusion of regressors (either linear or non-linear) in linear or semi-linear models. This allows the construction of the locally best invariant test, which in two important cases is equivalent to the one-sided t-test for a regression coefficient in an artificial linear regression model.

Keywords: Invariance; linear regression model; locally best invariant test; non-linear regression model; nuisance parameters; t-test. (search for similar items in EconPapers)
JEL-codes: C12 C2 (search for similar items in EconPapers)
Pages: 12 pages
Date: 2005
New Economics Papers: this item is included in nep-ecm
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