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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/223600
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- Deriving tests of the semi-linear regression model using the density function of a maximal invariant
- Bhowmik, Jahar L.; King, Maxwell L.
- 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
- Journal of Statistical Theory and Practice, Vol. 6, no. 2 (2012), pp. 251-259
- Publication year
- FOR Code(s)
- 0104 Statistics
- Invariance; Linear regression model; Locally best invariant test; Nonlinear regression model; Nuisance parameters; T-test
- Taylor & Francis
- Publisher URL
- 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