Minimum bias designs under random contamination: application to polynomial spline models
Minimum bias designs under random contamination: application to polynomial spline models
Minimising the bias due to model misspecification has long been a method for choosing designs. An approach is presented that incorporates prior knowledge of the possible form of the true model via an additive contamination term, regarded as a realisation of a random variable. This induces a random bias term for any given design. A prior distribution for the contamination is obtained either directly or from prior distributions for the individual elements of the contamination. A search technique is used to find designs, where properties of the bias distribution are estimated by simulation.
Several different criteria for choosing a design are proposed, motivated by the distribution of the bias. These criteria are investigated for models where the contamination has a polynomial spline form with uncertainty in the number of knots and their locations. The sensitivity of the resulting designs to the prior distributions is examined.
Woods, D. C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
17 May 2003
Woods, D. C.
ae21f7e2-29d9-4f55-98a2-639c5e44c79c
Woods, D. C.
(2003)
Minimum bias designs under random contamination: application to polynomial spline models.
Conference on New Directions in Experimental Design DAE 2003, Chicago, Illinois, USA.
14 - 17 May 2003.
Record type:
Conference or Workshop Item
(Other)
Abstract
Minimising the bias due to model misspecification has long been a method for choosing designs. An approach is presented that incorporates prior knowledge of the possible form of the true model via an additive contamination term, regarded as a realisation of a random variable. This induces a random bias term for any given design. A prior distribution for the contamination is obtained either directly or from prior distributions for the individual elements of the contamination. A search technique is used to find designs, where properties of the bias distribution are estimated by simulation.
Several different criteria for choosing a design are proposed, motivated by the distribution of the bias. These criteria are investigated for models where the contamination has a polynomial spline form with uncertainty in the number of knots and their locations. The sensitivity of the resulting designs to the prior distributions is examined.
More information
Published date: 17 May 2003
Venue - Dates:
Conference on New Directions in Experimental Design DAE 2003, Chicago, Illinois, USA, 2003-05-14 - 2003-05-17
Organisations:
Statistics
Identifiers
Local EPrints ID: 15835
URI: http://eprints.soton.ac.uk/id/eprint/15835
PURE UUID: 4057095d-25f1-4976-9cbb-32ee4a5fa1b0
Catalogue record
Date deposited: 06 Jun 2005
Last modified: 16 Mar 2024 03:14
Export record
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
