Electronic Journal of Statistics

Admissibility of the usual confidence interval in linear regression

Paul Kabaila, Khageswor Giri, and Hannes Leeb
Source: Electron. J. Statist. Volume 4 (2010), 300-312.

Abstract

Consider a linear regression model with independent and identically normally distributed random errors. Suppose that the parameter of interest is a specified linear combination of the regression parameters. We prove that the usual confidence interval for this parameter is admissible within a broad class of confidence intervals.

First Page: Show Hide
Primary Subjects: 62C15
Secondary Subjects: 62J05
Full-text: Open access
Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.ejs/1268230826
Digital Object Identifier: doi:10.1214/10-EJS563
Mathematical Reviews number (MathSciNet): MR2645486

References

[1] Casella, G. and Berger, R.L. (2002)., Statistical Inference, 2nd ed. Duxbury, Pacific Grove, CA.
[2] Farchione, D. (2009). Interval estimators that utilize uncertain prior information. Unpublished Ph.D. thesis, Department of Mathematics and Statistics, La Trobe, University.
[3] Joshi, V.M. (1969). Admissibility of the usual confidence sets for the mean of a univariate or bivariate normal population., Annals of Mathematical Statistics 40 1042–1067.
Mathematical Reviews (MathSciNet): MR264811
Zentralblatt MATH: 1166.62379
Digital Object Identifier: doi:10.1214/aoms/1177697608
Project Euclid: euclid.aoms/1177697608
[4] Joshi, V.M. (1982). Admissibility. On pp.25–29 of Vol. 1 of, Encyclopedia of Statistical Sciences, editors-in-chief, Samuel Kotz, Norman L. Johnson; associate editor, Campbell B. Read. John Wiley, New York.
Mathematical Reviews (MathSciNet): MR1044999
[5] Kabaila, P. and Giri, K. (2009). Confidence intervals in regression utilizing prior information., Journal of Statistical Planning and Inference 139 3419–3429.
Mathematical Reviews (MathSciNet): MR2549091
Zentralblatt MATH: 1167.62027
Digital Object Identifier: doi:10.1016/j.jspi.2009.03.018
[6] Kabaila, P. and Tuck, J. (2008). Confidence intervals utilizing prior information in the Behrens-Fisher problem., Australian & New Zealand Journal of Statistics 50 309–328.
Mathematical Reviews (MathSciNet): MR2474194
[7] Kempthorne, P.J. (1983). Minimax-Bayes compromise estimators. In, 1983 Business and Economic Statistics Proceedings of the American Statistical Association, Washington DC, pp.568–573.
[8] Kempthorne, P.J. (1987). Numerical specification of discrete least favourable prior distributions., SIAM Journal on Scientific and Statistical Computing 8 171–184.
Mathematical Reviews (MathSciNet): MR879409
Digital Object Identifier: doi:10.1137/0908028
[9] Kempthorne, P.J. (1988). Controlling risks under different loss functions: the compromise decision problem., Annals of Statistics 16 1594–1608.
Mathematical Reviews (MathSciNet): MR964940
Digital Object Identifier: doi:10.1214/aos/1176351055
Project Euclid: euclid.aos/1176351055
[10] Saleh, A.K.Md.E. (2006)., Theory of Preliminary Test and Stein-Type Estimation with Applications. John Wiley, Hoboken, NJ.
Mathematical Reviews (MathSciNet): MR2218139
Zentralblatt MATH: 1094.62024

2012 © Institute of Mathematical Statistics

Electronic Journal of Statistics

Electronic Journal of Statistics