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

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/157185

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 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 semilinear 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.
Publication type: Conference paper
Source: Paper presented at 'Statistics in the West', the Australian Statistical Conference (ASC 2010), including the 7th Australian Conference on Teaching Statistics (OZCOTS 2010), Fremantle, Western Australia, Australia, 06-10 December 2010
Publication year: 2010
Keyword(s): Maximal invariant statistics; Regression model; Semi-linear regression model; Testing
Publisher: Statistical Society of Australia
Publisher URL: http://www.promaco.com.au/2010/asc/
Publisher URL: http://www.statsoc.org.au/
Peer reviewed