Testing base load with non-sample prior information on process load

Khan, Shahjahan and Pratikno, Budi (2013) Testing base load with non-sample prior information on process load. Statistical Papers, 54 (3). pp. 605-617. ISSN 0932-5026

Abstract

Inference about population parameters could be improved using non-sample prior information (NSPI) from reliable sources along with the available data. This paper studies the problem of testing the intercept parameter of a simple regression model when NSPI is available on the value of the slope. The information on the slope may have the three different scenarios: (i) unknown (unspecified), (ii) known (certain or specified), and (iii) uncertain if the suspected value is unsure, for which we define the unrestricted test (UT), restricted test (RT) and pre-test test (PTT) for the intercept parameter. The test statistics, their sampling distributions, and power functions are derived. Comparison of the power functions and size of the tests are used to search and recommend a best test. The study reveals that the PTT has a reasonable dominance over the UT and RT both in terms of achieving highest power and lowest size.


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Item Type: Article (Commonwealth Reporting Category C)
Refereed: Yes
Item Status: Live Archive
Additional Information: © 2012 Springer-Verlag. Published online 3 May 2012. Permanent restricted access to Published version in accordance with the copyright policy of the publisher.
Depositing User: epEditor USQ
Faculty / Department / School: Historic - Faculty of Sciences - Department of Maths and Computing
Date Deposited: 30 Aug 2012 06:15
Last Modified: 14 Oct 2014 07:03
Uncontrolled Keywords: linear regression; test of intercept; power function; normal and bivariate student-t distributions
Fields of Research (FOR2008): 16 Studies in Human Society > 1603 Demography > 160399 Demography not elsewhere classified
01 Mathematical Sciences > 0104 Statistics > 010406 Stochastic Analysis and Modelling
01 Mathematical Sciences > 0104 Statistics > 010401 Applied Statistics
Socio-Economic Objective (SEO2008): E Expanding Knowledge > 97 Expanding Knowledge > 970101 Expanding Knowledge in the Mathematical Sciences
Identification Number or DOI: 10.1007/s00362-012-0451-4
URI: http://eprints.usq.edu.au/id/eprint/21581

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