A ray method of confidence band construction for multiple linear regression models
A ray method of confidence band construction for multiple linear regression models
This paper addresses the problem of confidence band construction for a standard multiple linear regression model. A “ray” method of construction is developed which generalizes the method of Graybill and Bowden [1967. Linear segment confidence bands for simple linear regression models. J. Amer. Statist. Assoc. 62, 403–408] for a simple linear regression model to a multiple linear regression model. By choosing suitable directions for the rays this method requires only critical points from t-distributions so that the confidence bands are easy to construct. Both one-sided and two-sided confidence bands can be constructed using this method. An illustration of the new method is provided.
329-334
Hayter, A.J.
55bd07a5-db1d-4d3d-8c87-b307485420d9
Liu, W.
b64150aa-d935-4209-804d-24c1b97e024a
Ah-Kine, P.
2553d7c8-99b4-492f-95ef-43c68e109737
1 February 2009
Hayter, A.J.
55bd07a5-db1d-4d3d-8c87-b307485420d9
Liu, W.
b64150aa-d935-4209-804d-24c1b97e024a
Ah-Kine, P.
2553d7c8-99b4-492f-95ef-43c68e109737
Hayter, A.J., Liu, W. and Ah-Kine, P.
(2009)
A ray method of confidence band construction for multiple linear regression models.
Journal of Statistical Planning and Inference, 139 (2), .
(doi:10.1016/j.jspi.2008.04.029).
Abstract
This paper addresses the problem of confidence band construction for a standard multiple linear regression model. A “ray” method of construction is developed which generalizes the method of Graybill and Bowden [1967. Linear segment confidence bands for simple linear regression models. J. Amer. Statist. Assoc. 62, 403–408] for a simple linear regression model to a multiple linear regression model. By choosing suitable directions for the rays this method requires only critical points from t-distributions so that the confidence bands are easy to construct. Both one-sided and two-sided confidence bands can be constructed using this method. An illustration of the new method is provided.
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Published date: 1 February 2009
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Statistics
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Local EPrints ID: 66096
URI: http://eprints.soton.ac.uk/id/eprint/66096
ISSN: 0378-3758
PURE UUID: 7ba3f9ab-b160-4b5c-8497-30b44c626bfe
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Date deposited: 28 Apr 2009
Last modified: 14 Mar 2024 02:35
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Author:
A.J. Hayter
Author:
P. Ah-Kine
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