Some robust designs for polynomial regression models | Zendy

Fang Zhide | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

Some robust designs for polynomial regression models

Author(s) -

Fang Zhide

Publication year - 2006

Publication title -

canadian journal of statistics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.804

H-Index - 51

eISSN - 1708-945X

pISSN - 0319-5724

DOI - 10.1002/cjs.5550340405

Subject(s) - mathematics , polynomial regression , polynomial , optimality criterion , degree (music) , regression , regression analysis , polynomial and rational function modeling , mathematical optimization , statistics , mathematical analysis , physics , acoustics

The author identifies static optimal designs for polynomial regression models with or without intercept. His optimality criterion is an average between the D ‐optimality criterion for the estimation of low‐degree terms and the D 8 ‐optimality criterion for testing the significance of higher degree terms. His work relies on classical results concerning canonical moments and the theory of continued fractions.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research