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Title

Deriving tests of the semi-linear regression model using the density function of a maximal invariant

Author(s)

Bhowmik, Jahar L.;  King, Maxwell L.

Abstract

In the context of a general regression model in which some regression coefficients are of interest and others are purely nuisance parameters, we define 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.We consider a specific semi-linear model to apply the constructed test.

Publication type

Journal article

Research centre

Swinburne University of Technology. Faculty of Life and Social Sciences

Source

Journal of Statistical Theory and Practice, Vol. 6, no. 2 (2012), pp. 251-259

Publication year

2012

FOR Code(s)

0104 Statistics

Keyword(s)

Invariance;  Linear regression model;  Locally best invariant test;  Nonlinear regression model;  Nuisance parameters;  T-test

Publisher

Taylor & Francis

ISSN

1559-8608

Publisher URL

http://dx.doi.org/10.1080/15598608.2012.673871

Copyright

Copyright © Grace Scientific Publishing, LLC. This is an Author's Accepted Manuscript of an article published in Journal of Statistical Theory and Practice (2012), available online at: http://www.tandfonline.com/10.1080/15598608.2012.673871. The accepted manuscript is reproduced in accordance with the copyright policy of the publisher.

Additional information

The authors acknowledge support from the Monash Research Graduate School and an Australian Research Council grant. An earlier version of this article was presented at the 2008 Australian Statistical Society Conference held in Melbourne, Australia.

Full text

Peer reviewed