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Exact simultaneous confidence bands for quadratic and cubic polynomial regression with applications in dose response study

Exact simultaneous confidence bands for quadratic and cubic polynomial regression with applications in dose response study
Exact simultaneous confidence bands for quadratic and cubic polynomial regression with applications in dose response study
Exact simultaneous confidence bands (SCBs) for a polynomial regression model are available only in some special situations. In this paper, simultaneous confidence levels for both hyperbolic and constant width bands for a polynomial function over a given interval are expressed as multidimensional integrals. The dimension of these integrals is equal to the degree of the polynomial. Hence the values can be calculated quickly and accurately via numerical quadrature provided that the degree of the polynomial is small (e.g. 2 or 3). This allows the construction of exact SCBs for quadratic and cubic regression functions over any given interval and for any given design matrix. Quadratic and cubic regressions are frequently used to characterise dose response relationships in addition to many other applications. Comparison between the hyperbolic and constant width bands under both the average width and minimum volume confidence set criteria shows that the constant width band can be much less efficient than the hyperbolic band. For hyperbolic bands, comparison between the exact critical constant and conservative or approximate critical constants indicates that the exact critical constant can be substantially smaller than the conservative or approximate critical constants. Numerical examples from a dose response study are used to illustrate the methods.
1369-1473
421-434
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Zhou, Sanyu
8b006abb-cfc9-4099-94b3-a6f9a034decf
Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0
Liu, Wei
b64150aa-d935-4209-804d-24c1b97e024a
Zhou, Sanyu
8b006abb-cfc9-4099-94b3-a6f9a034decf
Bretz, Frank
aa8a675f-f53f-4c50-8931-8e9b7febd9f0

Liu, Wei, Zhou, Sanyu and Bretz, Frank (2013) Exact simultaneous confidence bands for quadratic and cubic polynomial regression with applications in dose response study. Australian & New Zealand Journal of Statistics, 55 (4), 421-434. (doi:10.1111/anzs.12048).

Record type: Article

Abstract

Exact simultaneous confidence bands (SCBs) for a polynomial regression model are available only in some special situations. In this paper, simultaneous confidence levels for both hyperbolic and constant width bands for a polynomial function over a given interval are expressed as multidimensional integrals. The dimension of these integrals is equal to the degree of the polynomial. Hence the values can be calculated quickly and accurately via numerical quadrature provided that the degree of the polynomial is small (e.g. 2 or 3). This allows the construction of exact SCBs for quadratic and cubic regression functions over any given interval and for any given design matrix. Quadratic and cubic regressions are frequently used to characterise dose response relationships in addition to many other applications. Comparison between the hyperbolic and constant width bands under both the average width and minimum volume confidence set criteria shows that the constant width band can be much less efficient than the hyperbolic band. For hyperbolic bands, comparison between the exact critical constant and conservative or approximate critical constants indicates that the exact critical constant can be substantially smaller than the conservative or approximate critical constants. Numerical examples from a dose response study are used to illustrate the methods.

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Published date: 22 October 2013
Organisations: Statistics

Identifiers

Local EPrints ID: 369881
URI: http://eprints.soton.ac.uk/id/eprint/369881
ISSN: 1369-1473
PURE UUID: b863155c-61a5-44ac-8aba-5c7319977ccc
ORCID for Wei Liu: ORCID iD orcid.org/0000-0002-4719-0345

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Date deposited: 08 Oct 2014 10:31
Last modified: 15 Mar 2024 02:43

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Contributors

Author: Wei Liu ORCID iD
Author: Sanyu Zhou
Author: Frank Bretz

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