Optimal designs for regression models using the second-order least squares estimator

Simple item page
dc.contributor.authorYin, Yue
dc.contributor.authorZhou, Julie
dc.date.accessioned2017-07-31T18:55:05Z
dc.date.available2017-07-31T18:55:05Z
dc.date.copyright2017en_US
dc.date.issued2017-07-31
dc.descriptionThe final publication is expected to appear in Volume 27, Number 4, October 2017en_US
dc.description.abstractWe investigate properties and numerical algorithms for A- and D-optimal regression designs based on the second-order least squares estimator (SLSE). Several results are derived, including a characterization of the A-optimality criterion. We can formulate the optimal design problems under SLSE as semide nite programming or convex optimization problems and we show that the resulting algorithms can be faster than more conventional multiplicative algorithms, especially in nonlinear models. Our results also indicate that the optimal designs based on the SLSE are more e cient than those based on the ordinary least squares estimator, provided the error distribution is highly skewed.en_US
dc.description.reviewstatusRevieweden_US
dc.description.scholarlevelFacultyen_US
dc.description.sponsorshipThis research work is supported by Discovery Grants from the Natural Science and Engineering Research Council of Canada.en_US
dc.identifier.urihttp://dx.doi.org/10.5705/ss.202015.0285
dc.identifier.urihttp://hdl.handle.net/1828/8392
dc.language.isoenen_US
dc.subjectA-optimal design
dc.subjectconvex optimization
dc.subjectD-optimal design
dc.subjectmultiplicative algorithm
dc.subjectnonlinear model
dc.subjectSeDuMi
dc.subjecttransformation invariance
dc.subject.departmentDepartment of Mathematics and Statistics
dc.titleOptimal designs for regression models using the second-order least squares estimatoren_US
dc.typePreprinten_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Yin_Yue_StatisticaSinica_2017.pdf
Size:
861.7 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Faculty and Staff Publications
 
University of Victoria Libraries

We acknowledge and respect the Lək̓ʷəŋən (Songhees and Esquimalt) Peoples on whose territory the university stands, and the Lək̓ʷəŋən and W̱SÁNEĆ Peoples whose historical relationships with the land continue to this day.